www.maf.gov.om

OMAN SALINITY STRATEGY (OSS) SalinityStrategy AGRICULTURAL STATUS AND SALINITY IMPACT SALINITY ANNEX 2 2012

Oman Salinity Strategy

Annex 2

Agricultural Status and Salinity Impact

Prepared by Ministry Of And Fisheries (Maf), Sultanate Of Oman International Center For Biosaline Agriculture (Icba) Dubai, UAE

2012

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

ii

His Majesty Sultan Qaboos Bin Said

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

CONTRIBUTORS

International Center for Biosaline Agriculture (ICBA) Dr Shoaib Ismail (Leader) Dr Nanduri K. Rao

Ministry of Agriculture and Fisheries (MAF) Dr Ali Hussein Al‐Lawati (Co‐leader) Eng. Saif Ali Al‐Khamisi Dr Jamaan Rabeea Shamas Eng. Is’haq Omar Al‐Jabri Dr Naeem Al‐Shami Eng. Saud Saif Ali Al‐Habsi Dr Saleem K. Nadaf Eng. Hamed Sulaiman Al‐Dhuhli Dr Hamid Galoub Ali Eng. Eisa Rashid Al‐Ghairibi Eng. Saleh Ali Al‐Hinai Eng. Mariam Suleiman Al‐Azri Eng. Safa’a Al‐Farsi Eng. Nabeel Hassan Ebrahim Al‐Bahrini Eng. Fahad Al‐Rab’ani Eng. Hamdan Salem Al‐Wahaib Eng. Saif Salim Rashid Al‐Busaidi

Sultan Qaboos University (SQU) Dr Ahmed Al‐Busaidi

Ministry of Environment and Climate Affairs (MECA) Mr Salim Al‐Rubaiey

Other Organizations Mr Said Al‐Muselhi (Oman Wastewater Services Company‐Haya) Dr Hirayasu Onuma (Japan International Cooperation Agency) Dr Matsui Takehiko (Japan International Cooperation Agency)

International Consultant Dr Ed Barret‐Lennard (University of Western Australia)

 Currently with The Research Council (TRC) of the Sultanate of Oman.

i

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

ABBREVIATIONS AND ACRONYMS

AOAD Arab Organization for Agricultural Development DGALR Directorate General of Agriculture & Livestock Research ICARDA International Center for Agricultural Research in the Dry Areas ICBA International Center for Biosaline Agriculture IIASA International Institute for Applied Systems Analysis IPPM Integrated Production and Protection Management FAO Food and Agriculture Organization of the United Nations MAF Ministry of Agriculture and Fisheries, Oman MENA Middle East and North Africa MoA Ministry of Agriculture, Oman NARS National Agricultural Systems OSS Oman Salinity Strategy PA Protected Agriculture SGSL Sustainable Grazing of Saline Lands SQU Sultan Qaboos University SWRC Soil and Water Research Center

ii

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

CONTENTS

EXECUTIVE SUMMARY 1

1. OVERVIEW OF AGRICULTURAL PRODUCTION SYSTEMS IN OMAN 3 1.1. Agro‐climatic conditions 5 1.2. Crops and cropping pattern in 2010 6 1.3. Changes in cropped area and cropping pattern overtime 8 1.4. Changes in area by crop type and 10 1.5. Status of water and soil salinity in Al Batinah 13 1.5.1. Differentiating production by fresh, brackish and saline water areas 13 1.5.2. Salinity of ground water related to distance from the coastline 18 1.6. Status of water and soil salinity in 20 1.7. Crop‐livestock interaction 23 1.8. Main observations 23

2. ASSESSMENT OF CURRENT AGRICULTURAL PRODUCTION 25 2.1. Trends in agricultural production over time 25 2.2. Changes in production by crop type and governorates 27 2.3. Crop, soil and management 27 2.4. Trends in crop yields over time 28 2.5. Crop yields – Oman versus other countries 29 2.6. Main observations 31

3. IMPACT OF SALINITY ON AGRICULTURAL PRODUCTION 32 3.1. Loss of agricultural production due to salinity 32 3.1.1 OSS survey (2010, 2011) 33 3.1.2. FAO‐MAF study (2007) 38 3.1.3. Ministry of Agriculture (MoA) survey (2009) 38 3.1.4. Forage production database (2005‐2008) 39 3.1.5. Other evidence of loss in productivity due to salinity 41 3.2. Impact of irrigation on crop yield 42 3.3. Crop yields as affected by water and soil salinities 43 3.4. Spatial and temporal distribution of salinity versus crop yields 47 3.5. Impact on livestock 48 3.6. Main observations 48

4. AGRICULTURAL MANAGEMENT TO IMPROVE PRODUCTION SYSTEMS 49 IN AL BATINAH 4.1. Soil and water management 49 4.2. Improvement in crop varieties and their management 49 4.3. Crop diversification and alternate production systems 52 4.4. Protected agriculture 56 4.5. Integrated farming systems (crop‐livestock integration) 59 4.6. Main observations 60

iii

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

5. SHORT‐ AND LONG‐TERM ADAPTABILITY OF IMPROVED CROPS FOR SUSTAINABLE 61 YIELD PRODUCTION 5.1. Scenarios based on improving current agricultural systems 62 5.2. Technical and economic impacts of alleviating salinity by introducing 64 other production systems 5.3. Experience from other countries 65 5.3.1. Biosaline agriculture is now a recognized way of improving production 66 with saline resources 5.3.2. Integrated farming systems approaches are required to maximize 67 plant yield 5.3.3. Extension gaps between farmers and researchers can be overcome 67 using participatory approaches 5.4. Reducing the yield gap 68 5.4.1. How big are global yield gaps? 68 5.4.2. What contributes to the yield gaps? 70 5.4.3. Estimating crop yield potential 73 5.4.4. Approaches to study yield gaps 74 5.4.5. What can be done to reduce the yield gaps? 76 5.4.6. OSS perspective 77 5.5. Living with salinity and the role of biosaline agriculture 79 5.6. Main observations 82

REFERENCES 83

GLOSSARY OF TERMS 87

Appendix 1. Summary of agricultural statistics 88

Appendix 2. Soil salinity in Al Batinah governorates – Number and percentage of 96 farms under each salinity class

Appendix 3. Analysis of long‐term data on water salinity from 33 farms in 97 Suwaiq, Sahm and Barka Wilayats

Appendix 4. Yields of major crops in Oman and other MENA countries 104

Appendix 5. Leaching requirements for various crops grown with different 105 categories of saline water

Appendix 6. Case studies 106

iv

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

EXECUTIVE SUMMARY In the Sultanate of Oman, lower rainfall together with the over‐abstraction of ground water has dramatically increased the salinity problem in recent years. Realizing the seriousness of the problem, the Ministry of Agriculture (MAF) signed an agreement with the International Center for Biosaline Agriculture (ICBA) to develop a national strategy to combat salinity and protect water resources to sustain agricultural productivity in Oman. Formulating a strategy to manage salinity in Oman requires an assessment of the current agricultural situation and the extent to which increasing water and soil salinity are affecting crop yields and profitability. The current agricultural production in the Sultanate and the trend of change in cropped area, production, productivity over the years were assessed from the Agricultural Statistics Data (1997‐2010) and the Agricultural Census Reports (1992/93 and 2004/05). To discern the current status of soils and irrigation water salinity in Al Batinah, which is the main agricultural of Oman, surveys were undertaken and the data collected were compared with those from the South and North Batinah Integrated Studies (1993 & 1997, respectively) to analyze the trend of changes in salinity over the years. To assess the loss in agricultural production due to any increased salinity, a separate field survey was conducted in Al Batinah governorates in which sampling of crop yields and soil and water salinity at random were undertaken. Additionally, information from the FAO‐MAF survey (2007), empirical data from the Forage Project and other published information such as the Monograph on management of salt‐affected soils was drawn upon. Recommendations on the benefits to agricultural production from the adoption of improved management practices and salt‐tolerant germplasm were drawn from a desktop review of (a) the optimal practices to manage crop productivity, including irrigation (intensity, frequency and leaching fraction), soil health and nutrient status, and (b) the relative salt‐tolerance of plant species suited to Oman. While it is indeed true that major salinity problems do exist, the overwhelming conclusion from this study, is that the bulk of Oman’s agricultural sector is not constrained by salinity, but by other factors. Future activities therefore need to focus on improving both: (a) the existing agricultural system on land with good quality water and high potential productivity; and (b) demonstrating and implementing new agricultural opportunities for the use of salinized resources. The evidence for the effects of salinization in Al Batinah area is compelling. This report shows: (a) Thirty percent of the land has irrigation water with salinity (ECw) greater than 5 dS/m or 3500 ppm. A similar problem occurs in the Salalah . (b) The salinity of the is greatest in the area closest to the coast. (c) In affected areas, plant growth is strongly constrained by salinity and there appears to be a substitution of salt‐tolerant for salt‐sensitive species. (d) There has been abandonment of excessively salinized land.

However, the study also shows that most of the agricultural land in Al Batinah and Salalah governorates is not affected by salinity, having irrigation water with ECw less than 5 dS/m. Nevertheless, there is very considerable variation in yield on this land. The data on variation in the production of dates is compelling: in Al Batinah governorates the leading 10 percent of farmers in the OSS survey with water less than 3 dS/m (2,100 ppm) had yields that were 34‐fold higher than the yields of the lowest 10 percent of farmers. Furthermore, farmers that were able to achieve good yields with dates were also able to achieve good yields in other crops like alfalfa, mango and banana.

v 1

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Given this, Working Group 2 recommends two approaches for further project development in the Farming Systems area: 1. Benchmarking project – land of low salinity. A benchmarking project should be established on land of low salinity (ECw <4 dS/m or 2,800 ppm) to improve the productivity of existing agricultural systems. This project would be a partnership of farmer groups, the Ministry of Agriculture and other agencies (as required). Its aims would be to identify the most profitable and productive farmers, determine why their farming practices are successful, and then use participatory methods to encourage the trialing and adoption of those practices by other farmers. Because the project focuses on the improvement of existing agricultural systems, we expect that there would be rapid improvements in productivity across the agricultural sector. 2. Biosaline project – land of high salinity. A biosaline project should be established on land of high salinity (ECw >4 dS/m or 2,800 ppm) to develop new agricultural systems. This project would be a partnership of farmer groups working with the Ministry of Agriculture supported by international centers such as ICBA. Its aims would be to demonstrate a range of improved salt tolerant germplasm and management strategies (soil, water and cop) to improve production from moderately salinized resources, and then use participatory methods to encourage the trialing and adoption of those practices by other farmers. Because these technologies might appear foreign to many farmers and their benefits not readily apparent, it is recommended that this be a pilot project working initially with farmers in one highly salinized wilayat (e.g. Barka). Once the benefits of the biosaline approach are recognized the project could be ramped up at a later stage to spread the technologies to a broader farming constituency.

vi 2

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

1. OVERVIEW OF THE AGRICULTURAL PRODUCTION SYSTEMS IN OMAN The Sultanate of Oman is located in the southeastern part of the Arabian Peninsula between latitudes 16°40’N and 26°20’N and longitude 51°E and 59°40’E, and shares borders with the United Arab Emirates, Saudi Arabia, and the Republic of (Figure 1.1). The country has a coastline of almost 1,700 km, from the Strait of Hormuz in the north to the borders of the Republic of Yemen in the south‐west, overlooking three seas: the Arabian Gulf, the Gulf of Oman and the Arabian Sea. The Sultanate occupies about 309,500 sq. km equivalent to approximately 31 million hectares (ha).

With the exception of the , which has a strong monsoon climate and receives warm winds from the Indian Ocean, the climate of Oman is extremely hot and dry for most of the year. The highest temperatures occur in the interior, where readings of more than 53°C in the shade are common. The mean summer temperature in is 33°C, but gharbi, a strong wind that blows from the Rub al Khali Desert can raise temperatures by 6°C to 10°C. Winter temperatures are mild and pleasant, ranging between 18°C and 26°C. The average rainfall is about 100 mm, mostly distributed between November and February, except in the Dhofar governorate which receives from 200‐250 mm of rainfall during the monsoon in July‐ September.

Agriculture plays an important role in the country. The total cultivated area in 2010 was 172,071 feddans1 (72,270 ha), of which 92 percent is located in the coastal areas. Al Batinah coastal plain accounts for about two‐fifths of the land area under cultivation and is the most concentrated farming area of the country. Annual rainfall along the coast is minimal, but moisture falling on the mountains percolates through permeable strata to the coastal strip, providing a source of underground water which can be only about two meters below the surface. Diesel motors are used to pump water for irrigation from these shallow wells. By the mid‐1980s, the along Al Batinah coast had dropped to low levels, and salinity of the wells had increased, significantly reducing the . This was because of the combined effect of cultivating land too close to the sea and excessive pumping of well water, resulting in seawater intrusion.

In the early 1990s, farming areas in the interior accounted for more than one‐half of the country's cultivated land. Rainfall, although greater in the interior than along the coast, is insufficient for growing crops. Most of the water for irrigation is obtained through the falaj system, in which a vertical shaft is dug from the surface to reach water in porous rock. From the bottom of this shaft, a gently sloping tunnel is dug to tap the water and allow it to flow to a point on the surface at a lower level or into a cistern or underground pool from which it can be lifted by bucket or pump.

1 Feddan equals 0.42 hectare (ha), which is the conversion factor used throughout the document. 1 3

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

In Oman, farming systems include the production of crops as well as livestock. Farm holdings vary in size between less than 0.4 ha (one feddan) to more than 84 ha (200 feddans). About 11 percent of total farm holdings are less than 1.26 ha (three feddans), 65 percent are between 1.26 ha (three feddans) and 12.6 ha (30 feddans), and 23.8 percent are greater than 12.6 ha (30 feddans) (MoA, 2008). All the crops in Oman are irrigated except in the , where crops like and are rainfed. Irrigation is by flood, drip, bubbler or sprinklers.

Figure 1.1 Physiographic of Oman

Apart from water problems, the agricultural sector has been affected by rural‐urban migration, in which the labor force has been attracted to the higher wages of industry and the government service sector, and by competition from highly subsidized producers. As a result, agriculture and have declined in relative sectoral importance. In 1967 the two sectors together

2 4

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact contributed about 34 percent of GDP; by 1991 they accounted for 3.8 percent of GDP. The government encourages farming by distributing land, offering subsidized loans to purchase machinery, offering free feedstock, and giving advice on modern irrigation methods. As a result, the area under cultivation has increased, with an accompanying rise in total production. But extensive agricultural activity has also depleted freshwater reserves further and increased salinity of underground .

1.1. Agro‐climatic conditions The climate of Oman varies from arid to extremely arid in the interior part, humid in coastal areas and tropical in the southern parts. Two main agro‐climatic zones are recognized in the Sultanate based on land and water resources potential:  Northern Oman including Al Batinah Coastal plain, Interior Oman and Dhahirah plains, and Sharqiyah plains. • Southern Province (Dhofar) including Salalah plain, Dhofar Jebel and Najd.

Northern Oman Al Batinah Coastal plain By far the most important agricultural area in Oman is Al Batinah located between the Hajar mountain ranges and the Gulf of Oman. Al Batinah governorates account for over 50 percent of agricultural production, with the main crops being dates, crops, alfalfa, and forage crops. The climate of Al Batinah governorates is characterized generally by high temperatures reaching 48°C in the summer and mild temperatures ranging from 15°C to 24°C in the winter. The mean annual rainfall ranges from 76 to 100 mm. Over‐pumping of water in recent years has led to seawater intrusion and increased salinity of groundwater. As a result, some agricultural lands of the coastal areas have become unsuitable for cultivation.

Interior Oman and Dhahirah plains The interior plains lie within the inner foothills of the Hajar mountain ranges and include Buraimi plain, , Wadi Quriyat, and . The main crop is dates (9,463 ha), followed by alfalfa (38,368 ha) (MAF, 2005). The climate of this zone is characterized by high temperatures during summer. Nearly 20 percent of the total area under irrigation is served by the traditional falaj system and 74 percent by wells (MAF, 2005). The quality of the groundwater of the interior plains varies extensively, but most falaj water is generally of good quality.

Jebel Akdhar or Saiq Plateau Jebel Akdhar is a unique climatic zone because of the high altitude (reaching 3,000 m). Average summer temperatures are 30°C and the annual rainfall (300 mm) is significantly higher than elsewhere in Oman. The lower winter temperatures facilitate the cultivation of number of temperate deciduous fruit and nut trees such as pomegranates, peaches, apricots, apples, pears, walnuts and almonds.

3 5

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Sharqiyah Plains In Wadi Al Batha, agriculture is concentrated around Ibra, Ad Dariz, Al Ghabbi and Al Wafi. The area under crops is estimated to be 1,500 ha (3,570 feddans) in 26 oases irrigated mainly by the falaj system. The Sur plains have a very limited potential for development due to seawater intrusion. In contrast, the Wadi Batha plain offers the best potential for agriculture because of the existence of highly suitable soils associated with good quality groundwater in the Jalaan district around Al Kamil and Al Waif. Irrigation in this area is achieved by falaj systems. Private farms employ flood or furrow irrigation methods.

Southern Oman The southern part occupies approximately one third of the area of the Sultanate. Apart from the coastal plain extending from in the west past Salalah, the woody hills (reaching up to 1500 m elevation behind the plain) constitute a separate climatic zone. The southern slopes of the hills known as the ‘Jebel’ are rather steep, deeply incised narrow wadis, and receive southern monsoon . The northern slopes called ‘Najd’ are gentler and the wadis dissecting them are wider and less deeply incised.

Salalah plain Salalah plain is located in the coastal area of the southern province of Dhofar. Dhofar is the only region in Oman to benefit from the southern monsoon rainfall during July‐August. The average annual rainfall is about 110 mm but can range from 70 to 360 mm. Groundwater derived from aquifers in the central part of plain is of good quality. Irrigation practices and methods are similar to those employed in Al Batinah. Modern irrigation techniques are in operation in large commercial farms mainly for the production of forage crops such as Rhodes grass.

Dhofar Jebel The Jebel mountain ranges form a separate agro‐climatic zone of their own. Rainfall is particularly high, ranging from 600 mm to 700 mm, higher than any other area in the country, and this supports a permanent vegetation cover. The rainfed pasture land is concentrated on some half a million hectares on the Jebels Qara and Qamar. The Dhofar Jebel maintains two‐ thirds of the total cattle and one third of the total goat populations in the Sultanate.

Najd This area is underlain by an extensive carbonate . Water quality is generally poor and soils are structure less, of poor fertility and highly permeable. The temperature in Najd is higher than on the plain and the southern slopes. Najd has only traces of rainfall. Although the agricultural potential of these areas is limited, suitable areas of Najd with potential for agricultural development have been identified.

1.2. Crops and cropping pattern in 2010 In the Sultanate of Oman, the area under cultivation in 2010 was 172,071 feddans (72,270 ha), of which 51,801 (21,765 ha), i.e. 26.4 percent are under annual crops and the rest under perennial crops (see Appendix 1). Over half (51 percent) of the agricultural area is in Al Batinah

4 6

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Plain, followed by Sharqiyah which accounted for 14 percent of the area under cultivation. Fruit and forages occupied over 80 percent of the cultivated area (Table 1.1).

Table 1.1. Cultivated area (feddan) by crop type in different governorates in 2010 (Source: MAF/Agricultural Statistics, 2010). Governorate Vegetables Field Forage Fruit crops Total % crops crops Al Batinah 15,788 4,076 26,112 41,558 87,534 50.9 Dhahirah 1,053 2,834 5,183 8,198 17,268 10.0 Dakhiliyah 351 1649 2,400 11,403 15,803 9.2 Sharqiyah 1,118 517 7,273 15,944 24,852 14.4 Dhofar 104 726 10,540 4,622 15,992 9.3 Wusta 0 0 0 13 13 0.0 Buraimi 0 0 0 3,996 3,996 2.3 Muscat 51 160 819 3,961 4,991 2.9 Musandam 0 0 0 1,622 1,622 0.9 Total 18,465 9,962 52,327 91,317 172,071 100.0 A wide range of crops is cultivated in the Sultanate. The major crops and the area under cultivation in 2010 are shown in Table 1.2.

Table 1.2. Major crops and the area cultivated in 2010 (Source: MAF/Agricultural Statistics, 2010).

Crop Area Crop Area (feddan) Crop Area (feddan) (feddan) Vegetables Field crops Fruit Crops Tomato 3,408 Corn 8,816 Date palm 70,841 Watermelon 1,610 Barley 1,559 Banana 5,797 Pepper 1,522 Wheat 1,370 Lemon 2,860 Eggplant 1,276 Others 21,592 Mango 2,478 Cauliflower 1,125 Total 33,337 Coconut 1,069 Cabbage 864 Papaya 231 Potato 812 Forages Total 84,259 Cantaloupe 757 Rhodes grass 21,587 Squash 595 Alfalfa 13,366 Okra 587 Sorghum 2,752 Carrot 545 Others 2,867 Onion 472 Total 40,572 Garlic 147 Radish 142 Cucumber 85 Others 4,519 Total 18,465

5 7

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Overall, fruit crops occupied 53 percent of the area under cultivation, followed by forage (30 percent) and crops (11 percent). Field crops were grown on 6 percent of the area (Figure 1.2).

Vegetable crops Field crops Forage crops Fruit crops

11% 6%

53% 30%

Figure 1.2. Types of crops, area and percentage under cultivation in 2010 (Source: MAF/Agricultural Statistics, 2010). The major vegetables cultivated were tomato, water melon, pepper, eggplant, cauliflower and cabbage. Main field crops were corn, barley and wheat, while the major forages were Rhodes grass, alfalfa and sorghum. Among fruit crops, dates accounted for 84 percent of the area under fruit crops, followed by banana (7 percent). The cooler climate on the high plateau of the Al Jabal Al Akhdar reportedly enables the growing of apricots, grapes, peaches, and walnuts, however, the areas of cultivation of these crops were not available as they were all grouped under ‘other crops’ in the agricultural statistics data. Among vegetables, tomato accounted for 18 percent of the area, and among forages, Rhodes grass accounted for 53 percent of the area under cultivation.

1.3. Changes in cropped area and cropping pattern overtime Since 1970s, the overall area under cultivation in Oman increased by 106 percent, from about 66,360 feddans (27,882 ha) to 137,019 feddans (57,571 ha) in 1990, and by another 28 percent to 175,505 feddans (73,742 ha) in 1997. From 1997, however, the cultivated area declined by 7.3 percent from an average of 174,087 (73,145 ha) in the years 1997‐2000 to an average of 161,340 feddans (67,790 ha) in 2006‐10 (moving averages were used to smooth the data series and make it easier to spot trends). There were differences between governorates – while Dhofar, Sharqiyah and Dakhiliyah showed an increase; all other governorates (Al Batinah, Dhahirah, Wusta, Muscat and Musandam) registered a decrease in culltivated area. While Dhofar registered the highest increase by nearly 6,346 feddans, Al Batinah had the greatest reduction of 14,928 feddans in cultivated area from 1997‐2000 to 2006‐2010 (Figure 1.3A, B).

 Buraimi was excluded from the analysis, as data were available only from 2009. 6 8

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

200,000 A 180,000 160,000 140,000 Dhofar 120,000 Sharqiyah 100,000 Wusta (feddan)

80,000 Musandam Area 60,000 Muscat 40,000 Dakhiliyah 20,000 Dhahirah 0 Batinah 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year

10,000 B 5,000

‐

(5,000) (feddan)

Area (10,000)

(15,000)

(20,000)

Figure 1.3.A. Cropped area in Oman (1997 to 2010), and B. Change in cropped area between the years 1997‐2000 and 2006‐2010 (moving averages) (Source: MAF/Agricultural Statistics Data, 1997‐2010). Considering the crop type, field crops showed a 30 percent increase in cultivated area over the years 1997 to 2010, while vegetables, fruit and forage crops showed an overall decline of 14, 13 and 2 percent, respectively over the same period (Figure 1.4). The increase in field crop area was mainly due to the increased cultivation of ‘new’ crops such as corn in addition to the conventional crops like wheat, barley and sorghum.

7 9

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

1997‐2000 2001‐2005 2006‐2010

120,000 100,000 80,000 60,000 (feddan) 40,000

Area 20,000 0 Vegetables Field crops Perennial Fruit crops Forages

Figure 1.4. Crop types and area under cultivation (Source: MAF/Agricultural Statistics Data, 1997‐2010).

1.4. Changes in area by crop type and governorates Between 1997‐2000 and 2006‐2010, the area of vegetable crops declined marginally in all the governorates. The decline in the area was greatest in Dhofar (761 feddans), followed by Dhahirah (712 feddans) (see Appendix 1). For the field crops, all governorates except Dhahirah and Musandam showed an increase. While Dhofar had the greatest increase in cultivated area (4,730 feddans), Dhahirah showed the highest decline (2,290 feddans). In relation to forage crops, while Sharqiyah, Dhofar, Dakhiliyah and Musandam showed an increase in cultivated area, other governorates showed a decline. Sharqiyah showed the greatest increase (2,320 feddans) in forage area, while Al Batinah had the greatest decline of 3,047 feddans. With the fruit crops, Sharqiyah, Dhofar, Wusta and Musandam had an increase in cultivated area, in contrast to other governorates which showed a decline. The decrease in fruit crop area was considerably high for Al Batinah (12,230 feddans), followed by Muscat (1,862 feddans). Sharqiyah registered the greatest increase in fruit crop area (1,143 feddans) from 1997‐2000 to 2006‐2010 (Figure 1.5).

1997‐2000 2001‐2005 2006‐2010

60,000 50,000 40,000 30,000 (feddan) 20,000 10,000 Area 0

Figure 1.5. Change in area of cultivation of fruit crops (Source: MAF/Agricultural Statistics, 1997‐ 2010).

8 10

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Among vegetables, the cultivated area of tomato, cauliflower and eggplant was increased by 326, 319 and 62 feddans, respectively from 1997‐2000 to 2006‐2010 (Figure 1.6). However, there was a decrease in the area for all other major vegetables such as onion (1,501 feddans), potato (689 feddans), okra (398 feddans) and cucumber (167 feddans). All these crops, particularly onion, potato and okra are known for their sensitivity to salinity (see Steppuhn et al. 2005) and the decline in area of cultivation could be due to increased soil and water salinity.

1997‐2000 2001‐2005 2006‐2010 1997‐2000 2001‐2005 2006‐2010 1997‐2000 2001‐2005 2006‐2010 3,000 90,000 3,000 80,000 2,500 2,500 70,000 2,0002,000 60,000 50,000 1,500 (feddan)

1,500

(feddans) 40,000 (feddan)

1,000 30,000 1,000 Area Area Area 500 20,000 500 10,000 0 0 0 Date palm Banana Lemon Mango Coconut Papaya Other

Figure 1.9

Figure 1.6. FigureArea 1.of6 cultivation of major vegetable crops (Source: Agricultural Statistics/MAF, 1997‐2010).

Among the forage crops, the cultivated area increased for Rhodes grass by 38 percent, while that of alfalfa decreased by 40 percent from 1997‐2000 to 2006‐2010 at the Sultanate level (Figure 1.7).

1997‐2000 2001‐2005 2006‐2010

30,000

25,000

20,000

15,000 (feddan)

10,000 Area

5,000

0 Wheat Barely Alfalfa Rhodes grass

Figure 1.7. Change in area of cultivation of major field and forage crops (Source: MAF/Agricultural Statistics, 1997‐2010).

9 11

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Most notably, in Al Batinah governorates, the area of Rhodes grass increased by 115 percent, from 9,460 feddans in 1997 to 20,364 feddans in 2010, while that of alfalfa decreased by 79 percent – from 16,722 feddans to 3,580 feddans (Figure 1.8). It is also interesting to note that Dhofar governorate showed a nearly 300 percent increase in Rhodes grass area from 3,549 feddans in 2006 to 10,540 feddans in 2010. The reportedly growing demand for fodder in neighboring countries (mainly the United Arab Emirates, where cultivation of Rhodes grass was banned in the Abu Dhabi Emirate) could have contributed to the overall increase in Rhodes grass area, especially in the northern part.

Alfalfa Rhodes grass

30,000

25,000

20,000

15,000 (feddans)

10,000 Area 5,000

0

Years

Figure 1.8. Change in area of cultivation of alfalfa and Rhodes grass in Al Batinah governorates (Source: MAF/Agricultural Statistics, 1997‐2010). Among fruit crops, the area for papaya in the Sultanate (excluding Buraimi) increased by 459 feddans, followed by coconut (309 feddans) and banana (113 feddans). However, the cultivated area of dates, lemon and mango decreased by 10,657, 1,851 and 978 feddans, respectively (Figure 1.9). Both lemon and mango are known to be salt‐sensitive and the increased salinity of water could have been the reason for this decrease in area. Most notably, in the Al Batinah governorates, the area of all major fruit crops decreased from 1997‐2000 and 2006‐2010. Also of significance, the area of banana in the Dhofar governorate increased from 1,461 feddans in 2009 to 3,148 feddans in 2010 with similar increases in production. At the Sultanate level the banana area increased from 5,797 feddans in 2009 to 8,858 feddans in 2010. Without these increases, the overall decline in fruit crop area would have been much higher than that reported above.

10 12

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

1997‐2000 2001‐2005 2006‐2010

90,000 80,000 70,000 60,000 50,000 (feddan) 40,000 30,000 Area 20,000 10,000 0 Date Banana Lemon Mango Coconut Papaya Other palm fruits

Figure 1.9. Change in area of cultivation of major fruit crops (Source: MAF/Agricultural Statistics, 1997‐2010).

1.5. Status of water and soil salinity in Al Batinah Al Batinah accounts for slightly more than 50 percent of the agricultural area in Oman (Table 1.1) and recent studies have shown a decline in irrigation water quality and general deterioration of farming during the last two decades (Onuma, 2010). Salinity has been recognized as a huge threat to the sustainability of agriculture in the Sultanate of Oman, especially in Al Batinah area in a workshop held jointly by the Ministry of Agriculture (MOA) and International Center for Biosaline Agriculture (ICBA) in October 2009. The situation and the significance of salinity problem at that time were highlighted as: • The total salt affected area was 13.88 million ha, which was 44 percent of the total geographical area of Oman. • Some 1.56 million ha or 70 percent of the agriculturally suitable area were affected by salinity. • The annual losses due to salinity were reported as being US$19 to 36 million.

1.5.1. Differentiating production by fresh, brackish and saline water areas in Al Batinah An integrated study in three wilayats (Barka, Musannah and Suwaiq) in the south Batinah governorate in 1993 showed that 64 percent of the cultivated area was irrigated with saline water of less than 5 dS/m (Figure 1.10).

 1 dS/m equals 700 mg l‐1 or 700 ppm and 12 mmoles/l of NaCl. 11 13

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

16,000 14,000 12,000 10,000 8,000 6,000 (feddan) 4,000 2,000 Area 0 <2 2–3 3–5 5–7 7–10 10–15 15–20 >20 Salinity (dS/m)

Figure 1.10. Distribution of total cropped area and the salinity of irrigation water in South Batinah (Source: South Batinah Integrated Study, 1993).

A similar study, undertaken in 1997 in three wilayats (, Shinas and Liwa) of North Batinah also showed that 59 percent of the cultivated area was irrigated with saline water of less than 5 dS/m (Table 1.3).

Table 1.3. Salinity of cultivated area and irrigation water quality in North Batinah (Source: North Batinah Integrated Study, 1997). Irrigation Water Salinity (dS/m)/Number of farms Wilayat 0‐3 3‐5 5‐10 10‐20 >20 Total Sohar 1836 818 670 282 50 3656 % of total farms 50.2 22.4 18.3 7.7 1.4 100 Shinas 888 280 254 123 0 1545 % of total farms 57.5 18.1 16.4 8.0 0.0 100 Liwa 368 159 202 164 0 893 % of total farms 41.2 17.8 22.6 18.4 0.0 100

Soil and water salinity being highly dynamic and the integrated studies are dated back to mid nineties, a survey was undertaken in 2011 in Al Batinah governorates covering a total of 175 randomly selected farms from eight wilayats [henceforth referred as Oman Salinity Strategy (OSS) Batinah Survey, 2011] to assess the current status with irrigation water quality. The distribution of farms based on water salinity is presented in Table 1.4.

12 14

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 1.4. Water salinity and number of farms (Source: OSS Batinah survey, 2011). Number of farms with water salinity (dS/m) Wilayat <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Total Barka 7 3 2 3 3 1 4 6 29 % 24.1 10.3 6.9 10.3 10.3 3.4 13.8 20.7 100.0 Musannah 7 2 6 0 3 1 1 0 20 % 35.0 10.0 30.0 0.0 15.0 5.0 5.0 0.0 100.0 Suwaiq 11 7 4 2 2 2 0 0 28 % 39.3 25.0 14.3 7.1 7.1 7.1 0.0 0.0 100.0 Khaburah 7 2 2 1 3 0 4 1 20 % 35.0 10.0 10.0 5.0 15.0 0.0 20.0 5.0 100.0 Saham 9 2 4 1 1 1 1 1 20 % 45.0 10.0 20.0 5.0 5.0 5.0 5.0 5.0 100.0 Liwa 5 4 1 4 2 2 0 0 18 % 27.8 22.2 5.6 22.2 11.1 11.1 0.0 0.0 100.0 Sohar 10 4 1 2 2 1 0 0 20 % 50.0 20.0 5.0 10.0 10.0 5.0 0.0 0.0 100.0 Shinas 9 1 5 1 1 1 1 1 20 % 45.0 5.0 25.0 5.0 5.0 5.0 5.0 5.0 100.0 Total 65 25 25 14 17 9 11 9 175 % 37.1 14.3 14.3 8.0 9.7 5.1 6.3 5.1 100.0

From the above table, it is evident that 66 percent of the farms are being irrigated with water of less than 5 dS/m salinity, suggesting that the quality of groundwater has remained relatively similar since 1993. Nevertheless, a comparison of the water salinity data for the six wilayats from the current survey (2011) with those from the Integrated Studies of South (1993) and North Batinah (1997) suggests some differences in the salinity trend with time. In particular, the quality of water appears to have deteriorated considerably in Barka (Figure 1.11). It is important to stress that quite different survey methods were used in the two studies; however, the differences in the Barka wilayat are of such substantial scale that the effects appear to be real.

13 15

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

1993/1997 2011

70

60

50 farms

fo 40

30

20 Percentage 10

0 Barka Musannah Suwaiq Sohar Shinas Liwa

Figure 1.11. Percentage of farms or cultivated area irrigated with water of salinity >5 dS/m in 1993/1997 and 2011 in Al Batinah governorates (Note: The 2011 data are based on the data from the 175 farms surveyed as part of the OSS, while the 1993/97 data are based on the Integrated Studies covering the whole cultivated area (Barka, Musannah and Suwaiq) or all the farms (Sohar, Shinas and Liwa).

It is known that the quality of irrigation water influences crop productivity because of its effect on soil salinity. Therefore, to complement the irrigation water salinity data, soil salinity was also assessed in the eight wilayats both at the upper soil (0‐30 cm depth) and subsoil (30‐60 cm depth) (see Appendix 2). The summarized results presented in Table 1.5 below show that in about 54 percent of the farms soil salinity (ECe) both at the upper soil and subsoil was less than 5 dS/m. Above this threshold salinity, many traditional Omani crops do not grow well or will have low productivity.

Table 1.5. Soil salinity (ECe) at the upper soil (0‐30 cm) and subsoil (30‐60 cm) in Al Batinah area (Source: OSS Batinah survey, 2011).

0‐30 cm depth 30‐60 cm depth Salinity (dS/m) No. of farms Percentage Salinity (dS/m) No. of farms Percentage <2 62 29.5 <2 70 33.3 2‐3 16 7.6 2‐3 20 9.5 3‐5 36 17.1 3‐5 23 11.0 5‐7 15 7.1 5‐7 20 9.5 7‐10 11 5.2 7‐10 19 9.0 10‐15 21 10.0 10‐15 16 7.6 15‐20 4 1.9 15‐20 1 0.5 >20 10 4.8 >20 6 2.9 Total 175 100.0 175 100.0

14 16

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

The salinity of the upper soil was highly correlated with the salinity of the subsoil (P < 0.001; R2 = 0.61) (Figure 1.12). In contrast, the salinity of the irrigation water was less clearly related to soil salinity at both soil depths (R2 = 0.3‐0.4); despite this, the correlations were still significant at P < 0.001 (Figure 1.13 A&B). The poorer relationships between irrigation was salinity and soil salinity could be due to differences in the drainage status between individual farms, and differences in the amount of water applied to the crops; both these factors will affect the relative leaching or accumulation of salts in the soil, leading to “noise” in the correlations.

100 y = 1.267x ‐ 0.008 60 ‐ 80 R² = 0.725 30

at 60

40 cm

(dS/m) 20

0 0 10 20 30 40 50 60 Salinity Salinity (dS/m) at 0‐30 cm

Figure 1.12. Relationship between salinity in the upper soil (0‐30 cm) and subsoil (30‐60 cm) in Al Batinah farms (Source: OSS Batinah survey, 2011). The line of best fit was significant at P < 0.001.

60 A 50 y = 0.684x + 1.224 60 ‐ 40 R² = 0.420 30

at

30

(dS/m) 20 10 cm salinity 0 Soil 0 10 20 30 40 Water salinity (dS/m)

100 y = 0.861x + 1.580 B 30 ‐

0 80

R² = 0.300 at 60 40 cm(dS/m) salinity 20

Soil 0 0 10 20 30 40 Water salinity (dS/m)

Figure 1.13. Relationship between water salinity and soil salinity in the upper soil (A), and subsoil (B) in Al Batinah farms (Source: OSS Batinah survey, 2011). Both lines of best fit were significant at P < 0.001.

15 17

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 1.5.2. Salinity of the groundwater related to distance from the coastline Conceptually the groundwater of Al Batinah coastline consists of a lens of freshwater that moves from the hills towards the coast, overlying a layer of highly saline groundwater intruding from the coast. As groundwater is pumped from bores, saline and non‐saline water are both drawn towards the bore, and the degree of mixing of salt with depends primarily on the depth of the bore relative to the depth of the fresh/saline water interface (deep bores absorb more saline relative to fresh water) and the rate of water pumping (faster pumps absorb more saline relative to fresh water).

If within a locality neighbors use similar technologies for the withdrawal of water, and bores are dug to similar depths (based on local knowledge) and are pumped at similar rates, then other things being equal, we would expect to find: 1. The salinity of the groundwater would be higher closer to the coast than further away. 2. The rate of increase in salinity of the groundwater would be affected by distance from the coast. 3. The rate of salinization of the groundwater would decrease with time as the groundwater becomes more saline – as farmers would have less incentive to pump groundwater as the water becomes more saline.

Long‐term datasets for 33 farms with water salinity (ECw) values from three wilayats (Saham, Suwaiq and Barka), were obtained from the Agricultural Research Center and analyzed. Since all these farms have GPS coordinates, the ruler tool in Google Earth was used to estimate the distance from that location to the coast with an accuracy of ~ ± 0.02 km (see Table A3.1 of Appendix 3). The ECw measurements between March 2006 and December 2009 were used to calculate the average ECw ± SEM for each bore and the simple linear correlation parameters (slope, intercept and r2) for these data regressed against time. These parameters were then all related to distance from the coast. The analysis clearly shows that salinity of the groundwater (ECw) is related to seawater intrusion: average ECw increased exponentially with proximity to the coast for 33 farms across the three wilayats (Figure 1.14). However, the relationships varied between wilayats: at given distances from the coast, ECw values were highest in Barka wilayat and decreased in the order Barka > Saham > Suwaiq (Figure 1.14).

16 18

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

30 R² = 0.860 Suwayq (dS/m) 20 R² = 0.630 Saham ECw Barka 10 R² = 0.511 Expon. (Suwayq) Average Expon. (Saham) 0 Expon. (Barka) 0 5 10 Distance from coast (km)

Figure 1.14. Proximity to the coast increases averaage salinity of the groundwater – composite data for 3 localities monitored over 3 years. The exponential lines of best fit were all significant (Suwaiq, P <0.001; Saham, P = 0.005; Barka, P = 0.019). Rates of salinization (dS/m per year) were calculated from repeated measurements of ECw over three years. These trends were significant with time (P < 0.05) for 26 of the 33 farms monitored. For 25 of these farms the trend was for an increase in salinization; only 1 farm had a significant decrease in salinization with time. Rates of salinization were also exponentially related to distance from the coast for two of the three localities (Figure 1.15).

4 per 3 2 Suwayq (dS/m

1 Saham

year) 0 Barka

salinisation 0 2 4 6 Expon. (Suwayq)

‐1 of ‐2 Expon. (Saham)

Rate ‐3 Distance from coast (km)

Figure 1.15. Distance from the coast affects rates of salinization in the Suwaiq and Saham wilayats – composite dataset. There were significant trends in salinization with time for 26 of the 33 farms monitored. Proximity to the coast affected the rate of salinization for the Suwaiq (P = 0.044) and Saham (P = 0.027) wilayat. It is interesting that there is no relationship between rate of salinization of groundwater and distance from the coast for the Barka dataset (Figure 1.15). It may be because negative feedback in terms of farmer behavior affects the rate of salinization at high salinities. Figure 1.16 shows the relationship between the average salinity of the groundwater and the rate of water salinization for the three localities. It is interesting to see how most points sit on the same line as the average salinity of the groundwater increases from 0 to ~10 dS/m. Two farms in the Barka dataset had average salinities of the groundwater of 18 and 34 dS/m; these farms had quite

17 19

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact different rates of salinization to what would have been expected from the general dataset. Perhaps in each case the high salinity of the groundwater forced the farmers to adapt dramatically to the problem, relocating bores and/or using substantially less water which changed the rate of salinization. One would be greatly surprised not to see this kind of feedback in farmer behavior with highly saline groundwater.

4 3

of 2 year) 1 Suwayq per Saham salinisation

0 of

groundwater 0 10 20 30 40 Barka (dS/m ‐1 Rate ‐2 ‐3 Average ECw (dS/m)

Figure 1.16. Relationship between rate of water salinization and average salinity of the groundwater – composite dataset.

1.6. Status of water and soil salinity in Salalah In a similar manner to Al Batinah, a survey was undertaken in the Salalah (referred as OSS Salalah Survey, 2011) covering a total 161 randomly selected farms to assess the changes in water salinity over the years. The distribution of farms based on the water quality is presented in Figure 1.17 below. The salinity of irrigation water in about 40 percent of the farms was more than 5 dS/m, which could adversely affect the productivity of sensitive crops such as vegetables.

40 33.8% 35 30 25 22.5% Percentage 20 16.3% & 15 12.5% 10 5.0% 5.0% farms

3.8% 5 1.3% of 0 No. <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Water salinity (dS/m)

Figure 1.17. Distribution of water salinity in Salalah farms (Source: OSS Salalah survey, 2011).

18 20

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

To complement the water salinity data, soil salinity both in the upper soil (0‐30 cm) and subsoil (30‐60 cm) was also assessed on 80 farms. The results in Figures 1.18 A&B below show that in about 70 percent of the farms soil salinity both in the upper soil and subsoil is less than 5 dS/m. Similar to Al Batinah, the negative impacts on the productivity of many of the crops cultivated in Salalah are only expected on about 30 percent of the farms.

a 35 A 32.5% 30 23.8% 25 20 17.5% farms 15 10.0% of 7.5% 10 5.0% No. 5 1.3% 2.5% 0 <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Salinity (dS/m)

B B

40

30 29.4%

farm s 20.0% 21.2% 20 of 8.2% 7.1% 10 4.7% 4.7% 4.7% N o. 0 <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20

Salinity (dS/m)

Figure 1.18. Soil salinity (ECe values) in the Salalah farms: (A) upper soil (0‐30 cm), (B) subsoil (30‐60 cm) (Source: OSS Salalah survey, 2011).

In a similar manner to Al Batinah survey, there was a good correlation between the salinities of the upper soil and subsoil (R2 = 0.87; P < 0.001) (Figure 1.19). The regressions of water salinity against soil salinity were poorer but the lines of best fit were significant at P <0.001 (see Figure 1.20 A&B).

19 21

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Figure 1.19. Relationship between soil salinity (ECe values) in the upper soil (0‐30 cm) and the subsoil (30‐60 cm) in the Salalah farms (Source: OSS Salalah survey, 2011).

25 A cm 20 R² = 0.044 30 ‐ 0 15 at

10 (dS/m)

salinity 5

Soil 0 0 10 20 30 40 Water salinity (dS/m)

25

cm B 20

60 R² = 0.178 ‐

30 15

at 10 (dS/m) 5 salinity 0 Soil 0 10 20 30 40 Water salinity (dS/m)

Figure 1.20. Relationship between irrigation water and soil salinity in (A) the upper soil (0‐30 cm depth) and (B) the subsoil (30‐60 cm depth) in the Salalah farms (Source: OSS Salalah survey, 2011).

20 22

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 1.7. Crop‐livestock interaction Oman is the leading livestock producer in the Gulf region. Goats are the most numerous livestock species, followed by sheep, cattle and camel. The livestock numbers in the Sultanate, especially of goats, has increased considerably in the last five years. The total number of animals in 2009 stands at 2.4 million, which represents a 63 percent increase since 1996 (Figure 1.21). It means that more forage and fodder production is needed for feeding the livestock. Because non‐saline soils or fresh waters are mainly used for more economic and cash crops, there is a limitation for the development of forage crops in the Sultanate. Therefore, saline soils and waters are potential sources and can be devoted for forage production. To succeed in this approach, selecting suitable plant materials, implementing appropriate salinity management and proper use of forage products are crucial.

1,000 of

800

('000) 600

number

in 400

animals 200

Increase 0 Sheep Goats Camel Cattle Total

Figure 1.21. Changes in livestock number in Al Batinah governorates (Source: Agricultural Census Data, 1992/1993 and 2004/2005).

1.8. Main observations  The area under cultivation in 2010 was 172,071 feddans (72,270 ha), of which 26.4 percent is under annual crops and the rest under perennial crops. Over half (51 percent) of the agricultural area is in Al Batinah governorates. Fruit and forage crops comprised 80 percent of the total cultivated area.  The mean cultivated area declined by 7.3 percent from 1997‐2000 to 2006‐2010. Dhofar, Sharqiyah and Dakhiliyah showed an increase in cropped area, while all other governoratess (Al Batinah, Dhahirah, Wusta, Muscat and Musandam) registered a decrease.  Among the crop types, field crops showed a 30 percent increase in cultivated area over the years 1997 to 2010, while vegetables, fruit and forage crops showed an overall decline of 14, 13 and 2 percent, respectively over the same period.  A survey of 175 randomly selected farms from eight wilayats in Al Batinah governorates showed that some 66 percent of the farms are being irrigated with water of less than 5 dS/m salinity. Compared to 1993, the quality of water has deteriorated considerably in Barka.  Complementary studies of soil salinity in Al Batinah governorates showed that in about 54 percent of the farms, soil salinity (ECe) both at the upper soil and subsoil was less than 5 dS/m.

21 23

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

 The long‐term datasets for 33 farms from three wilayats (Saham, Suwaiq and Barka) showed that average groundwater salinity increased exponentially with proximity to the coast.  The livestock numbers, especially of goats has increased considerably in the last five years, with a simultaneous increase in the demand for feed. Since fresh water is mainly used for economic crops, saline water will be a potential source for forage production.

22 24

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 2. ASSESSMENT OF CURRENT AGRICULTURAL PRODUCTION Agriculture contributes only about 3 percent to GDP, but in recent times, Oman’s self‐sufficiency in the farm sector is said to be increasing. So far, Oman has reportedly achieved 51 percent self‐ sufficiency in vegetables, 71 percent in fruits, 24 percent in poultry meat, 52 percent in eggs and 58 per cent in milk (Anon, 2011). The contribution of local agricultural products to food security remained almost constant: 36 percent of the total consumption between 2000 and 2004, despite increase in population and the decrease of the harvested crop land in recent years because of salinity, drought and other problems (FAO/AQUASTAT, 2008). While agricultural production has improved greatly since 1970s, water shortage in some governorates, salinity increase in wells and surface irrigation are limitative factors in terms of productivity.

2.1. Trends in agricultural production over time Between 1985 and 1990, overall agricultural production increased by 3 percent from 678,030 tonnes2 to 699,000 tonnes. Between 1990 and 1997 agricultural production increased substantially (by 76 percent) reaching 1,232,400 tonnes. There was a general decrease in agricultural production in subsequent years, as it fell from an average of 1,232,528 tons over 1997‐2000 to an average of 1,174,278 tons over 2006‐2010. While this represents an overall decrease of 58,250 tonnes (i.e. 4.7 percent) at the Sultanate level, Al Batinah had the greatest decline of 45,659 tonnes, followed by Dhahirah (25,802 tonnes), Muscat (16,952 tonnes) and Wusta (820 tonnes) among the governorates (Figure 2.1).

30,000 20,000 10,000 0 ‐10,000 (tonnes) ‐20,000 ‐30,000 ‐40,000 Production ‐50,000 ‐60,000 ‐70,000

Figure 2.1. Change in agricultural production in Oman from (1997 to 2010) (Source: MAF/Agricultural Statistics, 1997‐2010).

One of the problems with representing total production, as above, is that this does not show how crops may be substituted to achieve changes in total production. We therefore focus here

2 Metric ton, equal to 1,000 kilograms (kg).  Buraimi was excluded from analysis as data were not available for the years before 2009. 23 25

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact on production within the major agricultural product categories. In 2010, forages represented 58 percent of the volume of the total agricultural production in Oman, followed by fruit crops (23 percent) and vegetables (17 percent) (Figure 2.2). Among the forage crops, Rhodes grass accounted for 77 percent of the production. Among the fruit crops, dates accounted for 76 percent of the production, followed by banana (16 percent).

Vegetable crops Field crops Forage crops Fruit crops

23% 17% 2%

58%

Figure 2.2. Crop type and production percentage in 2010 (Source: MAF/Agricultural Statistics, 2010).

Between 1997‐2000 and 2006‐2010 all crop types except field crops showed a decrease in production ranging between 47,028 tonnes (forages) and 7,757 tonnes (vegetables) (Figure 2.3). It should be noted that the decrease in total production of fruit crops was despite a considerable increase in the area of cultivation of date palm and banana. The increase observed in field crop production was mainly due to the large‐scale cultivation of corn and other crops in the Dhofar governorate in 2009 (Figure 2.3). Thus, the area and production of field crops in 2009 were 22,056 feddans and 32,112 tonnes respectively, whereas in 2008, these figures were only 577 feddans and 845 tonnes, respectively. Excluding the increases in 2009, the average area and production of field crops in 2006‐2010 were higher by only 1 and 5 percent (respectively) than those recorded during 1997‐2000.

10,000

0 Vegetables Field crops Perennial Fruit crops ‐10,000 Forages (tonnes) ‐20,000

‐30,000

Production ‐40,000

‐50,000

Figure 2.3. Change in production of different crop types from 1997‐2010 (Source: MAF/Agricultural Statistics, 1997‐2010).

24 26

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 2.2. Changes in production by crop type and governorates Between 1997‐2000 and 2006‐2010, the production of vegetable crops declined in all governorates except Al Batinah which showed a small increase (1,303 tonnes). The decline in vegetable production was greatest in Dhofar (9,192 tonnes), followed by Dhahirah (2,664 tonnes), Sharquiyah (2,485) and Dakhiliyah (2,029 tonnes). For the field crops, all the governorates except Dhahirah and Musandam showed an increase in production. Dhofar had the greatest increase in production (6,977 tonnes) which coincides with the increased area of cultivation. In relation to the forage crops, while Sharqiyah, Dhofar and Dakhiliyah showed an increase in production, other governorates showed a decline. Among the governorates, while Sharqiyah showed greatest increase (31,368) in forage production, Al Batinah had the greatest decline of 69,147 tonnes, followed by Dhahirah (18,966 tonnes) and Muscat (13,865). With regard to fruit crops, production has increased in Al Batinah, Dhofar, Muscat and Musandam in contrast to other governorates which showed a decline. The increase in fruit production was considerably high (21,569 tonnes) in Al Batinah, followed by Dhofar (6,631 tonnes). Sharqiyah registered the greatest decline in fruit production (9,461 tonnes) from 1997‐2000 to 2006‐2010 (Figure 2.4). Interestingly, fruit crop production in Al Batinah increased by 16 percent, despite a 23 percent decrease in the cultivated area, while in Sharqiyah fruit production decreased by 15 percent despite some 8 percent increase in the cropped area (see Figure 1.5).

25,000

20,000

15,000

10,000 (tonnes) 5,000

0 Production ‐5,000

‐10,000

‐15,000

Figure 2.4. Change in production of fruit crops from 1997 to 2010. (Source: MAF/Agricultural Statistics, 1997‐2010).

2.3. Crop, soil and irrigation management All of the data synthesized, including the surveys do not provide any indication of the specific management options being practiced in the production systems. Furthermore, no information was available on the irrigation practices and the crop varieties cultivated, both from the past as well as the recent surveys. This seems to be a major reason to interpret the significant variation in yield data reported for the different crops from 1999‐2010, where the same crops at similar

25 27

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact salinity levels showed a big range in yield. This leads to the conclusion (discussed in more detail in Section 5) that information related to the soils and water management practices are vital and needs to be recorded to prepare any future plans to mitigate the effect of salinity. Another gap identified was the lack of soil salinity data. Data collected and analyzed for the last 10 years do not provide any substantial and reliable information on soil salinity.

All agricultural areas are irrigated from groundwater sources. While the area under sprinkler and localized irrigation has tripled over the last 10 years, the traditional surface irrigation system remains the most common irrigation technique covering almost 80 percent of the area equipped for irrigation in 2003. Sprinkler and localized irrigation systems, also called modern irrigation systems as opposed to traditional surface or flood irrigation systems, are mainly found on new farms (FAO, 2009). The amount of water used for irrigation depends on the type of crop and the cropping system adopted, as well as on the climate of the governorates. It varies from 16,700 to 20,800 m3ha‐1year‐1 depending on the governorate and from 4,000 to 27,400 m3 ha‐1 year‐1 according to the type of crop. The net return on water from agriculture is generally marginal in northern Oman. In Salalah returns are much better because crop water requirements are lower and higher value crops, such as banana and coconut are grown.

2.4. Trends in crop yields over time While salinity can affect gross agricultural production, yields (tonnes per hectare) of crops, especially those sensitive to salinity can be a good indicator of the negative effect. Despite the general trend of decrease in area and production, yields between the years 1997‐2000 and 2006‐ 2010 showed an overall increase of 2.25 percent at the Sultanate level. Among the governorates, Al Batinah registered a 10.2 percent increase in yield (despite a 15 percent decline in area and a 2 percent decline in production), while Wusta had the greatest reduction of 61 percent, followed by Dhofar (Figure 2.5). The reasons for the improvement in yields in Al Batinah governorates are not clear, but it is possible that introduction of improved germplasm both for yield and salinity tolerance and the adoption of better crop management practices could have been important. However, a more detailed analysis would be necessary to confirm this.

2 1 0 ‐1 ‐2 ‐3 (tonnes/feddan) ‐4 ‐5 ‐6

Productivity ‐7 ‐8

Figure 2.5. Change in agricultural yields (tonnes/feddan) in different governorates of Oman (Source: MAF/Agricultural Statistics, 1997‐2010).

26 28

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Among the different types of crops, vegetables, field and fruit crops showed an overall increase in yields, while forages showed a decrease during 2006‐2010 in comparison with 1997‐2000 (Figure 2.6). Introduction of improved germplasm and adoption of better management practices could have been the reason for the increase in productivity in vegetable, field and fruit crops. However, no details were available on the crop varieties introduced and grown by the farmers over the years to elucidate the contribution of genotypes in the increased yields.

0.6 0.4 0.2 0

(t/feddan) ‐0.2 Vegetables Field crops Perennial Fruit crops ‐0.4 Forages ‐0.6 ‐0.8 Productivity ‐1 ‐1.2

Figure 2.6. Change in yield according to crop type (Source: MAF/Agricultural Statistics, 1997‐ 2010)

2.5. Crop yields – Oman versus other countries Crop yields during any particular season will depend largely on the interaction of the crops’ genetic makeup (genotype), soil, cultural and environmental factors. Although growers (farmers) have little control over some environmental factors, especially weather, their selection of an appropriate site and the cultural practices will help achieve good yields. In order to assess the overall performance of the agricultural sector in Oman, we compared the yields of some of the major crops obtained in 2008 with those from eight other countries in the MENA region (i.e. United Arab Emirates, Kuwait, Saudi Arabia, Tunisia, Morocco, Libya, Jordan and Syria) and also with the attainable good yields under irrigated and intermediate input conditions (see Appendix 4). From Figure 2.7A, it is evident that the yields of several crops such as barley, wheat, sorghum, potato, onion, okra, water melon and dates in Oman were higher, while those of lemon, carrot, tomato, cucumber3 etc. were lower than the average yields reported from other countries in the region. Averaged over crops, the yield in Oman was 4.5 percent less than the regional average. Compared to the good yields attainable with irrigated and intermediate input conditions, all crops except cauliflower had lower yields, with an overall deficit of 27 percent in terms of aggregate yield (Figure 2.7B).

3 Although average productivity of cucumber was low, with two crops per year, maximum yields close to 10 t/greenhouse/year (which amounts to 277 t/ha/year, considering that each greenhouses is close to 360 m2) were reported, while one farmer growing four crops obtained a total of 19.75 t/greenhouse/year (i.e. ~550 t/ha/yr) (see ICARDA/APRP, 2010). 27 29

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

a All crops A

Barley

Dates

Wheat

Watermelon

Cauliflower

Cucumber

Lemon

‐100 ‐50 0 50 100 150 200 Difference between Oman and regional yield (%)

B All crops B Cauliflower Tomato Okra Eggplant Cucumber Dates Potato Watermelon Onion Sorghum/Millet Barley Wheat Carrot Lemon

‐100 ‐80 ‐60 ‐40 ‐20 0 20 40 60 Difference between Oman and global yield (%)

Figure 2.7. Differences in the yields of the major crops cultivated in Oman with (A) the average yields obtained in eight countries of the MENA region in 2008 and (B) with attainable good yields under irrigated/intermediate input conditions (Source: AOAD, 2009; FAO/IIASA, 2000).

28 30

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 2.6. Main observations  Gross agricultural production in Oman fell by 4 percent from 1997 to 2010. Al Batinah had the greatest decline (6 percent), followed by Dhahirah, Muscat and Wusta.  Except for the field crops, other types of crops, namely vegetables, forage and field crops showed a 4‐6 percent decrease in production.  In 2010, forages represented 58 percent of the volume of the total agricultural production, followed by fruit crops (23 percent) and vegetables (17 percent).  The mean crop yield in Oman was 4.5 percent less than the regional aggregate average. However, compared to the globally reported good yields with irrigated and intermediate input conditions, the aggregate yield was less by 27 percent.  Despite the general trend of decrease in area and production, agricultural productivity (yield per unit area), showed an overall increase of 2.25 percent, possibly due to the introduction and adoption of improved germplasm and better crop management practices.

29 31

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

3. IMPACT OF SALINITY ON AGRICULTURAL PRODUCTION Soil and water salinity is reportedly emerging as the most significant problem of present‐day agriculture in the Sultanate of Oman. Over‐pumping of ground water in the past three decades is said to have increased the salt concentrations of both inland and coastal aquifers. Aquifers near the coast are believed to be affected the most; many of them becoming highly saline to the extent that they are not suitable for growing sensitive crops.

3.1. Loss of agricultural production due to salinity The critical parameter that causes changes in plant growth in saline soils is the salinity of the soil solution; this is directly affected by the concentration of salts in the soil, and inversely affected by the concentration of moisture in the soil. In irrigated situations, the concentration of salt in the soil will be affected by the salinity of the irrigation water and the degree to which irrigation is supplied in sufficient excess to leach salt that accumulates in the root‐zone into the subsoil. However, the concentration of moisture in the soil is also affected by irrigation; if it is too little, the soil dries out, potentially increasing the salinity of the soil solution manifold.

In general soil salinity is measured as the electrical conductivity of the saturation extract (termed the ECe). This is a measure in which soil salinity at a standardized level of moisture (saturation), a condition that only occurs when the soil is waterlogged. Mostly soils are at less than saturation so the salinity of the soil solution is greater than the ECe. By definition, the salinity of the soil solution equals the ECe at saturation, and as a rule of thumb it is approximately twice the ECe at field capacity, and approximately 4 times the ECe at wilting point (Richards, 1954). Given this, in hot arid countries, we might expect better relationships between ECe and yield, than between ECw and yield.

Not surprisingly, irrigation water quality (affecting soil salinity) can have profound effects on crop production. There are many studies worldwide which show that increasing soil salinity reduces the growth and yield potential of crops. Maas and Hoffman (1977) and their successors – most recently Maas and Grattan (1999) – approximate these growth curves in terms of two parameters, a point up to which salinity has no adverse effect on the relative yield of a crop (termed the threshold concentration) and a slope term (as percent reduction in relative yield per dS/m) defining the degree of decrease in yield for each dS/m increase in ECe above the threshold. More recently, Steppuhn et al. (2005a,b) have pointed out that these “bent stick” curves of Maas and Hoffman only provide a rough approximation of plant responses to increasing salinity, and the crop growth response curve is better modeled using a “discount curve” defined by the concentration at which the 50 percent decrease in yield occurs and a curve steepness parameter. Both Maas and Grattan (1999) and Steppuhn et al. (2005b) have published an extensive list of coefficients describing the salinity responses of a number of horticultural and agronomic crops.

The previous section of this report showed that the salinity of water used for irrigation in 40‐50 percent of the farms is more than 5 dS/m and this increases soil salinity on average by 0.7 to 0.9 dS/m as compared to irrigation water; therefore, with the exception of a few salt‐tolerant crops such as date palm and Rhodes grass, the productivity of most crops cultivated in Oman is expected to decrease. Table 3.7 provides a list of coefficients for Maas and Hoffman style curves relating ECe and ECw to relative growth (or yield) for a range of crop species cultivated in Oman. 30 32

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

To determine the relation between crop productivity and salinity in an agricultural area and to assess the extent and degree of salinity problems, it is normal practice to undertake field surveys, sampling crop yields and soil salinity at random and then perform an appropriate statistical analysis of the data obtained. A number of earlier reports from the Ministry of Agriculture, Japanese International Cooperation Agency, North and South Batinah Integrated Studies, etc. were synthesized for the yield data of the important crops, in order to assess the relationship with salinity (soil and water). However, it was generally felt that: 1. Many parameters that were important to establish the linkages were not collected, or not available and if available, un‐reliable even. 2. Methodologies for obtaining the data were incorrect and/or inadequate and also different standards were used for measurements etc., by different teams/surveys. 3. Most often, the salinity (especially soil) data were missing, though yield data are available and vice versa.

The absence of sufficient data on crop yields in relation to farm salinity necessitated to plan and conduct a comprehensive survey for updated information and for filling the gaps. A detailed questionnaire was prepared in coordination with the other working groups and a field survey was conducted in six wilayats of Al Batinah governorates by the Ministry of Agriculture, Oman.

The following section gives a description of the synthesized data based on the following four datasets: 1. Oman Salinity Strategy (OSS) Batinah Survey (2010‐2011) 2. Food and Agriculture Organization of the United Nations (FAO)‐Ministry of Agriculture and Fisheries (MAF) Study (2007) 3. Ministry of Agriculture (MoA) Survey (2009) 4. Forage project database (2005‐2008)

3.1.1. OSS surveys (2010‐2011) As part of the present work, a survey was conducted in 2010 in six wilayats of Al Batinah governorates (referred as OSS Batinah survey, 2010) to assess crop productivity in relation to the quality of water used for irrigation in Oman. Besides an in situ measurement of water and soil quality on 370 farms, information on the crops being grown, area and the production (gross yield) was gathered using the questionnaire presented in Appendix 1. A summary of the irrigation water salinity and crop yield data obtained in the survey is presented in Table 3.1 below.

Table 3.1. Range in the salinity of irrigation water and yields of major crops (Source: OSS Batinah Survey, 2010). Crop Number of Irrigation water salinity (dS/m) Yield (tonnes/feddan) farms Range Mean+SD Range Mean+SD Date palm 323 0.4‐15.8 2.7+2. 7 8.8‐0.1 2.3+1.7 Mango 100 0.6‐12.1 1.6+1.4 17.7‐0.2 3.3+4.0 Lemon 65 0.5‐12.1 2.8+4.1 40.0‐0.1 4.0+9.2 Banana 83 0.6‐7.3 1.7+1.2 140.0‐0.4 9.6+20.0 Tomato 38 0.5‐6.3 1.6+1.3 63.1‐0.1 14.5+14.2 Pepper 26 0.6‐4.6 1.6+1.2 45.0‐0.3 13. 9+14.9 Lettuce 28 0.75‐6.6 3.0+2.0 15.0‐0.5 4.1+3.6 Alfalfa 163 0.6‐13.2 3.0+2.4 125.0‐0.1 9.3+15.7

31 33

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

An analysis of the data obtained from the survey showed that the salinity of irrigation water in the farms ranged between 0.4 and 15.8 dS/m. There was wide variation in the yield (production per unit area) of crops recorded from different farms having the same level of salinity of irrigation water and a plot of the data on the productivity versus salinity of the irrigation water showed considerable scatter (see Figure 3.1A). It became obvious that the yield of date palm in many farms was considerably low even when irrigated with good quality water. For instance, in farms with water salinity of <3 dS/m, the date palm yields ranged from 0.1 tonnes to 8.8 tonnes (per feddan). More importantly, 55 percent of these farms had only one‐third of the maximum recorded yield (Figure 3.1B) and the leading 10 percent of farmers obtained yields averaging 7.2 tonnes that were 34‐times higher than the yields (averaging 0.2 tonnes) of the lowest 10 percent of farmers. Similar yield variations were also found to be true for many other crops under cultivation in Oman (data not presented). The extreme variation in yields observed in low‐ salinity farms was presumably because of the presence of other production factors such choice of cultivar, soil type, nutrient status, the quantity of water applied to leach salts from the root‐ zone and other management practices. The yield anomalies in the low‐salinity farms can be substantially reduced by adopting appropriate crop, soil and water management strategies together with educating the famers with relevant information and technology.

30 B

of of 30

f 10 A f 25 o 2025 8 20 15

(%) 15 6

(%) 10 10 frequency frequency

4 requency 5 f f 5

farms 00 farms ve

2 i (tonnes/feddan)

at 20 30 40 50 60 70 90 80 80 10 20 30 40 50 60 70 80 90 10 l ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ Relative Relative ‐ 100 100

0 e ‐ 0 ‐ 0 RR l i 10 20 30 40 50 60 70 70 80 10 20 30 40 50 60 70 80 Yield 90 0 5 10 15 20 90 Water salinity (dS/m) Percentage ooff maxium yieeldld

Figure 3.1. Relationship between irrigation water salinity and yield of date palm (A) Source data (B) Relative frequency of farms and the percentage of maximum recorded yield at irrigation water salinity of

Devoid of information on crop, soil and water management, moving‐average method was used to smoothen the data and assess the changes in productivity with increase or decrease in water salinity. Accordingly, the data were sorted on salinity into subsets of 1 dS/m interval (0.1–1.0, 1.1–2.0, 2.1–3.0…. 15.1–16.0) and for each subset, the mean yield (tonnes per feddan) was calculated and plotted against the mean salinity as shown in Figure 3.2. From the figure, it can be seen that productivity of all crops decreased linearly with increase in salinity. The rate of decline with increase in salinity varied among crops and differed from the typical crop yield response to increasing salinity described by Maas and Hoffman’s (1977) threshold‐slope model. This is not entirely unexpected because unlike controlled experiments, growth conditions especially the nutrient status and irrigation levels vary considerably in farmer’s fields and by interaction of these factors, the relations are subjected to large degree of variation. Nevertheless, the observed trends for all the major crops provided sufficient indication of the negative effects of salinity on crop productivity.

32 34

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Date palm A Mango BF 3.5 4 y = ‐0.1639x + 2.5757 y = ‐0.5057x + 4.0954 3.5 2 3 2 R = 0.699 R = 0.8286 3 2.5 2.5 2 2 (tons/feddan) 1.5 1.5 (tons/feddan)

1 Yield 1

Yield 0.5 0.5 0 0 0 1 2 3 4 5 ‐0.5 0 5 10 15 20 Water salinity (dS/m) Water salinity (dS/m)

Lemon C Banana D 6 14 y = ‐0.192x + 4.2198 y = ‐3.0925x + 14.476 12 2 5 R2 = 0.7809 R = 0.9878 10 4 8 3 (tons/feddan)

(tons/feddans) 6

2 4 Yield Yield 1 2 0 0 0 5 10 15 20 25 0 1 2 3 4 5 Water salinity (dS/m) Water salinty (dS/m)

Alfalfa E Tomato 16 F y = ‐1.0122x + 11.603 25 14 y = ‐4.2176x + 19.387 R2 = 0.6709 12 20 R2 = 0.821 10 15 8 6 10 (tons/feddan) (tons/feddan) 4

2 5 Yield 0 Yield 0 ‐2 0 2 4 6 8 10 12 14 0 1 2 3 4 5 6 ‐4 ‐5 Water salinity (dS/m) Water salinity (dS/m)

Pepper G Lettuce H 25 7 y = ‐5.2325x + 21.271 y = ‐0.7031x + 6.1988 6 20 R2 = 0.8415 R2 = 0.907 5 15 4 (tons/feddan) 3 10 (t/feddan)

yield 2 5 Yield 1

0 0 0 1 2 3 4 5 0 1 2 3 4 5 6 7 ‐5 Water salinity (dS/m) Water salinity (dS/m)

Figure 3.2. Relationship between salinity of irrigation water and yield of some major crops grown in Oman (Source: OSS Batinah survey, 2010).

From the above figures, it is evident that productivity of sensitive crops such as mango, banana and most vegetables, is reduced by as much as 50 percent by increase in irrigation water salinity from 1 to 3 dS/m. Among all crops, date palm appeared to be more tolerant to salinity than the others. Banana was found to be least tolerant to salinity than the other fruit crops and showed

33 35

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact grater reduction in yield for unit increase in salinity. While vegetables in general appeared to be highly sensitive to salinity compared to fruit crops, lettuce was found to be relatively more tolerant than other vegetables. Alfalfa, with significant reduction in yield per unit increase in salinity, showed greater sensitivity to salinity than reported in the literature.

Cropping pattern versus water salinity in Al Batinah The distribution of the major crops by water or soil salinity based on the recent surveys (in 2010 and 2011) is presented in Tables 3.2 and 3.3. The cropping pattern shows that fruit crops and forages dominate at higher salinities. Apart from date palm which is known to be moderately tolerant, sensitive fruit crops like mango, banana and lime were also documented at higher salinities. After the date palm, alfalfa and Rhodes grass were the most common crops found at the higher salinities, which is not unexpected because of their relative tolerance to salinity compared to other crops. Vegetables are mostly grown on farms with <5 dS/m water salinity, though occasionally found at higher salinities.

Table 3.2. Distribution of main crops (percentage of farms for each crop) versus irrigation water salinity in Al Batinah (Source: OSS Batinah survey, 2010).

Irrigation water salinity (dS/m) Crop <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 Date palm 33.1 41.2 36.2 44.1 64.7 71.4 100.0 Mango 14.6 10.3 8.6 0.0 0.0 7.1 0.0 Lime 10.3 8.1 6.9 7.4 0.0 0.0 0.0 Banana 11.6 12.5 7.8 5.9 5.9 0.0 0.0 Onion 0.2 1.5 0.9 1.5 0.0 0.0 0.0 Tomato 6.0 1.5 4.3 2.9 0.0 0.0 0.0 Pepper 3.4 3.7 2.6 1.5 0.0 0.0 0.0 Musk melon 2.4 1.5 0.0 1.5 0.0 0.0 0.0 Water melon 1.5 0.7 1.7 0.0 0.0 0.0 0.0 Cucumber 1.3 0.0 2.6 0.0 0.0 0.0 0.0 Cabbage 1.7 0.7 0.9 1.5 0.0 0.0 0.0 Alfalfa 14.0 18.4 27.6 33.8 29.4 21.4 0.0 Total (%) 100.0 100.0 100.0 100.0 100.0 100.0 100.0

34 36

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 3.3. Distribution of main crops (percentage of farms for each crop) versus soil salinity in Al Batinah (Source: OSS Batinah survey, 2011).

Soil salinity at 0‐30 cm (dS/m) Crop <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Date palm 28.2 31.0 33.3 37.9 37.0 45.2 33.3 63.2 Banana 11.4 19.0 8.9 6.9 3.7 2.4 16.7 0.0 Mango 9.4 4.8 7.8 17.2 7.4 9.5 0.0 10.5 Lime 5.4 2.4 2.2 6.9 3.7 2.4 0.0 0.0 Pepper 1.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Squash 6.7 0.0 0.0 0.0 3.7 2.4 0.0 0.0 Pumpkin 2.0 0.0 0.0 0.0 0.0 0.0 0.0 5.3 Eggplant 3.4 2.4 0.0 0.0 0.0 0.0 0.0 0.0 Water melon 0.7 2.4 1.1 0.0 0.0 0.0 0.0 0.0 Muskmelon 2.0 0.0 1.1 0.0 0.0 0.0 0.0 0.0 Cowpea 2.0 0.0 2.2 10.3 0.0 0.0 0.0 0.0 Other vegetables 0.0 4.8 4.4 0.0 0.0 2.4 33.3 0.0 Alfalfa 10.7 16.7 11.1 3.4 11.1 9.5 16.7 0.0 Rhodes grass 15.4 16.7 24.4 17.2 29.6 23.8 0.0 21.1 Millets 1.3 0.0 3.3 0.0 3.7 2.4 0.0 0.0 Total (%) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Cropping pattern versus water salinity in Salalah The distribution of the major crops by water salinity based on the recent survey of 56 farms in Salalah is presented in Table 3.4. The data show that coconut and Rhodes grass were the most common crops documented at higher salinities, which is not unexpected because of their relative tolerance to salinity. However, sensitive fruit crops like papaya and banana were also being grown at higher salinities, which makes their production economically unviable.

Table 3.4. Distribution of main crops (percentage of farms for each crop) versus irrigation water salinity in Salalah (Source: OSS Salalah survey, 2011).

Crop Water salinity (dS/m) <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Papaya 0.0 18.7 2.8 8.3 10.0 0.0 0.0 100 Coconut 0.0 25.0 38.9 33.3 30.0 40.0 20.0 0.0 Banana 33.0 25.0 33.3 25.0 40.0 0.0 0.0 0.0 Lemon 67.0 25.0 2.8 0.0 0.0 0.0 0.0 0.0 Rhodes grass 0.0 6.3 22.2 33.3 20.0 60.0 80.0 0.0 Total (%) 100 100 100 100 100 100 100 100

35 37

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

3.1.2. FAO‐MAF study (2007) In 2007, the Ministry of Agriculture in collaboration with the Food and Agriculture Organization of the United Nations (FAO) conducted a survey of 112 randomly selected farms in four wilayats (Barka, Suwaiq, Saham and Sohar) of Al Batinah. For 34 of the 112 farms, the yield data of Rhodes grass and date palm were analyzed with respect to well water salinity. The crop yields when regressed against water salinity showed no relationship (see Figures 3.3 A & B). This was probably because the salinity of irrigation water in the farms was low (much below the threshold salinity values of 4.0 and 4.6 dS/m for date palm and Rhodes grass respectively, according to Maas and Hoffman’s bent stick model) to observe any significant impact on the yield.

70 A 60

50

40 (kg/tree) 30 20 Yield 10 0 0 1 2 3 4 Water salinity (dS/m)

60,000 B 50,000 40,000 30,000 20,000 (kg/feddan) 10,000

Yield 0

0 2 4 6 8 Water salinity (dS/m)

Figure 3.3. Yields (in kg/feddan) of (A) Date Palm and (B) Rhodes grass from Barka, Al Suwaiq, Saham and Sohar wilayats (Source: FAO‐MAF study, 2007).

3.1.3. Ministry of Agriculture (MoA) Survey (2009) The Ministry of Agriculture (MoA) in previous years has selected 580 farms on a random basis in Al Batinah governorates for customary statistical surveys (henceforth referred to as the MoA survey). All these farms have geographic coordinates, but the information on soil or water salinity was unavailable. Some 118 of these farms had yield data for crops under cultivation in 2009 and cross‐referencing of the geographic coordinates with those of the 370 farms (which had information on water salinity) from the OSS survey, identified 31 farms common in both the surveys. In order to assess the relationship between salinity and crop productivity, the crop yield data from the MOA survey in 2009 were plotted against the water salinity data from the OSS survey in 2010. The results of liner regression shown in Figure 3.4 indicate no effect of salinity

36 38

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact on crop yield. However, it should be pointed out that in the majority of farms, water salinity was very low and in fact below the threshold values (as per Maas and Hoffman’s model) to observe any negative impact on productivity in respective crops.

Figure 3.4. Relationship between salinity of irrigation water and crop yield (Source: MoA Survey, 2009).

3.1.4. Forage project database (2005‐2008) The fodder demand in the Sultanate is mostly met by local production of Rhodes grass, alfalfa and some annual forage cereals and legumes. However, the existing cultivars of these are not very salt‐tolerant. The increasing demand for fodder and the general deterioration in the quality of soil and water quality have necessitated the Ministry of Agriculture to identify alternative varieties and/or crops that produce high biomass yield under saline conditions. In a collaborative project (hereafter referred as the Forage Project) with the International Center for Biosaline Agriculture (ICBA), several cultivars of salt‐tolerant crops such as pearl millet, sorghum, fodder beet and canola were evaluated for their fodder productivity between 2004 and 2008 (see MoA/Comprehensive Report 2005‐2008). A summary of information on the salinity of irrigation water and the green forage yields obtained over the years in field trials conducted in Rumais Agricultural Research Station is presented in Figure 3.5 below. It can be seen that in

37 39

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact barley, canola and fodder beet, green forage yields were clearly correlated with the salinity of the irrigation water (Figure 3.5).

A 40 R² = 0.931 30 yield

20 (t/ha)

forage 10 0 Gree 10 12 14 16 18 Salinity (dS/m) B

80 R² = 0.946 B

yield 60

40

forage 20 (t/ha)

0

Green 5 10 15 20 25 Salinity (dS/m) C 150

R² = 0.950 C 100 yield

50 forage (t/ha) 0 10 15 20 25 Green Salinity (dS/m)

Figure 3.5. Relationship between irrigation water salinity and crop yield A. Barley, B. Fodder beet and C. Canola (Source: ICBA’s Projects in Oman, Comprehensive Report 2005‐2008).

As part of the Forage Project, five genotypes of pearl millet selected for superior performance were further evaluated to study their response to four levels of irrigation water salinity under field conditions for two consecutive years during the summer seasons of 2007 and 2008. The results indicated significant to highly significant effects of years and salinity (P < 0.05 and P < 0.01, respectively) for the various characters such as plant height, tiller number, leaf width and green and dry matter yields (Nadaf et al., 2010). There was no significant effect of genotype in these experiments, probably because all the cultivars were already of superior performance, having been selected for high yields under salinity in previous trials. There was a gradual but insignificant decrease in fresh and dry matter yields as irrigation water salinity increased from low salinity control conditions to 6 dS/m. However, from 6 to 9 dS/m, there was a significant (35‐40 percent) reduction in the dry matter production in all the genotypes (Figure 3.6).

38 40

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Control (0.8 dS/m) 3 dS/m 6 dS/m 9 dS/m

12 10

8 (t?ha) 6

Yield 4 2 0 IP 19587 Sudan Pop IIIIP 6104 IP6112 IP 3616

Genotype

Figure 3.6. Effect of salinity of the irrigation water on dry matter yield of five salt‐tolerant genotypes of pearl millet (Source: Nadaf et al., 2010).

3.1.5. Other evidence of loss in production due to salinity Alfalfa productivity under saline conditions Al Lawati et al. (2010) evaluated the performance of alfalfa for biomass yield and water use efficiency under different regimes of irrigation water salinity (1, 3 and 6 dS/m) under field conditions. Water use efficiency was higher at 1 dS/m and generally decreased with increasing water salinity levels. The cumulative fresh biomass yields after nine cuts at 3 and 6 dS/m salinity were reduced by about 12 percent, compared to 1 dS/m (Figure 3.7).

1 dS/m 2 dS/m 3 dS/m

40 35 30 (kg/m2) 25 20 yield 15 10 Green 5 0 125 Etc 100 Etc 75 ETc Total

Levels of irrigation

Figure 3.7. Effect of irrigation water salinity and irrigation levels on fresh biomass production in alfalfa. Water was provided at the rates of 75, 100 and 125 percent of the crop

Evapotranspiration value (ETC) (Source: Al Lawati et al., 2010).

Abandoned farms From the farmer’s standpoint, economic viability is the most important consideration to continue his farming activities. Increases in soil salinity can make the farms uneconomical for cropping and in the longer run, unfit for agricultural use leading to their abandonment. Besides

39 41

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact the direct evidence of loss of production with increases in salinity presented above, there is also evidence of the abandonment of farms in prime agricultural areas of Oman (Tables 3.5 and 3.6). For instance, the South and North Batinah Integrated Studies in 1993 and 1997 (respectively) reported that nearly 3,000 ha of date palm and other crops had been abandoned. The main cause of abandonment was stated to be decreasing yields and quality of products due to increasing irrigation water salinity, although there could have also been other factors such as land‐use change, urban expansion, etc.

Table 3.5. Abandonment of date palm crops in South Batinah (Source: South Batinah Integrated Study, 1993).

Barka Musannah Suwaiq Total

Ha % Ha % Ha % Ha % Active Date palm 2,254 84 1,452 83 1,367 73 5,073 80 Abandoned 441 16 289 17 502 27 1,232 20 Date palm All Date palm 2,695 100 1,741 100 1,869 100 6,305 100

Table 3.6. Abandonment of crops in North Batinah (Source: North Batinah Integrated Study, 1997).

Sohar Shinas Liwa Total

Ha % Ha % Ha % Ha % Date Palm 608 98 759 88 486 97 1853 94

Other crops 15 2 100 12 14 3 130 6 Total 623 100 859 100 500 100 1981 100

3.2. Impact of irrigation on crop yield Different types of irrigation system are known to influence the crop yield, mainly due to the efficiencies of the system together with the quality of water used. Flood irrigation has an efficiency of 60 percent whereas drip irrigation shows 85 percent efficiency. However the choice of the irrigation system is also related to the crops being grown. Among the major crops grown, date palm, mango and lime are irrigated by bubbler irrigation and the forage grasses with sprinkler system. Other crops, including vegetables are mainly irrigated through drip irrigation.

Specific information of irrigation system versus the crop is unclear from the available data, including those from the recent OSS survey. Many farms are shown using modern irrigation system (drip, sprinkler and bubbler), but the details of the crops and their yields were not available.

40 42

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Figure 3.8 shows that from 2005 onwards, the areas irrigated by flooding has reduced, especially in Saham and Sohar. In Suwaiq, and Barka, more than 90 percent of the area is now being irrigated with modern irrigation system. In Suwaiq, around 50 percent is irrigated with drip irrigation only, whereas in Barka, bubbler and sprinkler irrigation methods contribute 32 and 39 percent, respectively. The data points for Khaburah do not provide much information from the farms surveyed and hence negligible percentage of modern irrigation system and around 98 percent of flood irrigation is depicted. It should be noted that the data for 2010 are from the OSS survey from the representative farms whereas those of 2005 are from the Agricultural Census for the whole country.

Figure 3.8. Comparison of flood and modern (drip, sprinkler and bubbler) irrigation system used in Oman.

3.3. Crop yields as affected by water and soil salinities In salt affected areas, an effective use of available soil and water resources requires the cultivation of agricultural crops that are relatively tolerant to salinity. To do this, reliable information is needed to predict crop yields in response to various levels of salinity in the root‐ zone. Based on extensive literature search, Maas and Hoffman (1977) concluded that crop yield as a function of the average root zone salinity could be described reasonably well with a piecewise linear response function characterized by a salinity threshold value below which the yield is unaffected by soil salinity, and above which yield decreases linearly with salinity. The threshold‐slope model has proved to be extremely useful for a variety of applications including crop planning and management. Table 3.7 below lists the threshold and slope values for major agricultural crops in terms of ECe. The data are only indicative of the relative tolerance of different crops and apply only where crops are exposed to uniform salinities from seedling stage to maturity.

41 43

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 3.7. Salt tolerance of major agricultural crops of Oman (Source: FAO, 1985).

Crop Threshold (dS/m) Slope (% per dS/m) Field crops Barley 8.0 5.0 Wheat 6.0 7.1 Sorghum 6.8 16.0 Corn 1.7 12.0 Vegetables Tomato 2.5 9.9 Cucumber 2.5 13.0 Potato 1.7 12.0 Pepper 1.5 14.0 Eggplant 1.1 6.9 Cabbage 1.8 9.7 Onion 1.2 16.0 Carrot 1.0 14.0 Lettuce 1.3 13.0 Radish 1.2 13.0 Cantaloup 2.2 Fruit crops Date palm 4.0 3.6 Lemon 1.5 12.8 Banana Forages Alfalfa 2.0 7.3 Rhodes grass 4.6 ‐

For the major crops cultivated in Oman, the approximate soil salt concentration (ECe), at which 10, 25 and 50 percent yield decrease may be expected is presented in the Table 3.8. The zero‐ yield decrease represents the threshold value at which salinity begins to affect crop yields. The data are based on published information based on averages of representative crop varieties. Actual yield reductions may vary depending upon the variety planted, soil characteristics and environmental and water management practices during the growing season. However, it should be noted that Maas and Hoffman’s threshold values provide a rough estimation of plant response to increasing salinity. Van Genuchten and Gupta (1993) and Steppuhn et al. (2005) showed that these thresholds do not exist as there is an ever‐decreasing loss in productivity with increasing salinity and an alternative S‐shaped response mode provides a better description of the yield response of crops to salinity. Accordingly, Steppuhn et al. (2005) computed the C50 values, a parameter which describes the degree of salt tolerance of the crop (average root‐zone salinity at which the yield declines by 50 percent) after re‐analyzing over 200 data sets from experiments around the world. Table 3.8 also provides the C50 values for the major crops in Oman.

42 44

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 3.8. Soil salinity (expressed as electrical conductivity of saturated paste extract, ECe) and potential yield reduction for selected crops grown in Oman (Source: Ayers and Westcot, 1985; Evans, 2006; Steppuhn et al., 2005).

Crop Relative yield decrease (%) @ 10 25 50 C50 Field crops Barley (Forage) 10 13 18 12.6 Wheat (Bread) 7.4 9.5 13 2.8*‐12.6** Wheat (Durum) ‐ ‐ ‐ 5.3*‐18.6** Sorghum 5.1 7.2 11 9.6 Corn (Forage) ‐ ‐ ‐ 8.2 Corn (Sweet) 2.5 3.8 5.9 5.5

Vegetables Tomato 3.5 5.0 7.6 7.2 Cucumber 3.3 7.6 6.3 6.0 Potato 2.5 3.8 5.9 5.5 Pepper 2.2 3.3 5.1 4.8 Eggplant 1.6 ‐ ‐ 8.0 Cabbage 2.8 4.4 7.0 6.6 Onion 1.8 2.8 4.3 4.0 Carrot 1.7 2.8 4.6 4.3 Lettuce 2.1 3.2 5.2 4.8 Radish 2.0 3.1 5.0 4.7 Muskmelon 3.6 5.7 9.1 6.6 Fruit crops Date palm 6.8 10.9 17.9 17.4 Lemon 2.3 3.2 4.8 5.1 Banana 2.3 3.2 ‐ ‐ Forages Alfalfa 3.4 5.4 8.8 8.5 Rhodes grass 6.6 ‐ ‐ ‐ * Dryland; **Irrigated; @Root‐zone salinity at which yield declines by 50 percent as estimated by S‐shaped response curve (Steppuhn et al. 2005)

The data presented in Section 3.1.1 clearly showed that excessive soil salinity reduces yields, ranging from slight loss to complete failure, depending on the crop and the severity of the salinity problem. Salinity‐induced crop yield loses may often be minimized by adopting soil and water management and agronomic practices that are appropriate for the local soil, crop and environmental conditions. Unfortunately, high salinities are sometimes difficult to prevent and it

43 45

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact is not economically practical to recover low soil salinity levels. Under such conditions, choosing a suitable salt‐tolerant crop can minimize crop loss due to salinity. The numerous field and laboratory experiments conducted over the past 50 years or so have resulted in salt‐tolerance lists of various crops (see Table 3.9 below).

Table 3.9. Grouping of plants with respect to their salt tolerance potential (Adapted from Hussain, 2005). The salinity interpretation is according to the general format used for OSS.

Tolerant Moderately tolerant Moderately Sensitive Sensitive (ECe 6‐8 dS/m)* (ECe 4‐6 dS/m) (ECe 2‐4 dS/m) (ECe <2 dS/m) Barley Fig Alfalfa Almond Bermuda grass Guar Cabbage Apple Date palm Jujube Capsicum Apricot Kallar grass Oats Cauliflower Bean Sugar beet Papaya Corn Carrot Tall wheatgrass Pomegranate Cucumber Grapefruit Rape Eggplant Lemon Rhodes grass Grapes Lime Rye Lettuce Mango Sorghum Sweet melon Okra Soybean Potato Onion Sudan grass Pumpkin Orange Wheat grass Radish Peas Cowpea Sesbania Peach Sesame Spinach Pear Olive Sugarcane Plum Cotton Sunflower Rice Wheat Sweet potato Strawberry Chikoo Tomato Avocado Barseem Turnip Cherry Water melon Pineapple Pepper Squash

*Salinity interpretation is according to the general scheme adopted for the OSS. For conversion: 700 ppm = 1 dS/m.

44 46

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 3.4. Spatial and temporal distribution of salinity versus crop yields The problem of soil and water salinization, especially in the coastal areas of Al Batinah, has been realized as early as 1985. The groundwater equilibrium was upset due to the arid tropical conditions and total dependence upon groundwater withdrawals from wells in the absence of surface water: first by the transition from animal bailed to pumped wells, and subsequently by agricultural expansion and increasing urban and industrial water demand. The consequent effects of increased saline intrusions have been monitored over the years. Between 1987 and 1997 the Ministry of Agriculture and Fisheries (MAF) represented by the Directorate General of Agriculture and Livestock Research at Rumais (DGALR) conducted a national soil survey, followed by detailed studies of soil, water and land cover in the agricultural areas of coastal Al Batinah. The large change in water quality of a few wells about five kilometers from the coastal area of Al Batinah is illustrated in the Table 3.10 below.

Table 3.10. Water quality changes from 1994‐2004 (Source: Al‐Rasbi, 2009).

Year Salinity (dS/m) Well 1 Well 2 Well 3 Well 4 Well 5 1994 4.07 1.42 6.77 5.57 1.01 1995 6.09 1.40 7.99 6.40 1.04 1996 9.09 1.86 9.48 8.29 1.03 1997 10.2 2.68 10.2 11.9 1.34 1998 15.7 3.37 10.5 15.3 1.01 1999 18.5 3.77 9.35 19.1 1.01 2000 19.8 5.26 8.00 26.6 1.03 2001 25.2 5.36 7.80 29.5 1.06 2002 26.6 10.2 10.5 33.5 1.08 2003 31.4 11.3 9.45 38.1 1.10 2004 33.5 12.5 ‐ 38.6 1.11

It has been realized that yields are gradually decreasing on the farms under cultivation and the problem is becoming so acute to make the farming economical. Although, no recent data are available to show the extent of present salinity and the losses occurring to the agriculture of the country, Hussain (2005) made some assessment based on the area under different land utilization types and the gross margin values from Integrated Studies of Batinah in 1993 and 1997. It was estimated that annual losses occurring from soil salinity to the country range from 6.7 to 13.3 million Omani Riyal (OMR). If the loss of abandoned date palm farms is included then the losses will be ranging in between 7.3 and 14.0 million OMR per annum.

45 47

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 3.5. Impact on livestock Increased water salinity, besides reducing the availability of feed and the feed quality, will directly affect the livestock production, since the animal has little or no capacity to store excess salts sodium and chloride in the body or to secrete them out. High levels of sodium in the diet reduces organic matter digestibility, depresses appetite and the efficiency of energy use, leading to significant reduction in productivity and ultimately the number of livestock. There was an increase in all categories of animals from 1996 to 2009, despite the reduction seen in both the area and productivity of forages in the region (Figure 3.9). It is interesting to note that there was 68 percent increase in the number of goats from 2004 to 2005 and the reasons for this are not clear.

2,000

1,500 ('000) Sheep 1,000 Goats animals 500 of Camel 0 Cattle 1996 1998 2000 2002 2004 2006 2008 Number Year

Figure 3.9. Livestock number in Oman (Source: Agricultural Statistics, MAF).

3.6. Main observations  Extreme variation was observed in the crop yields obtained from different farms, though having the same level of water salinity.  Crop yields of in majority of farms were considerably low even when irrigated with good quality water. In date palm, 55 percent of the farms with water salinity of <3 dS/m (considered as non‐saline) have less than a third of the maximum recorded yield.  Adoption of appropriate crop, soil and water management practices is expected to improve the yields significantly in the low‐salinity farms.  Analysis of the cropping pattern in Al Batinah and Salalah shows that sensitive fruit crops like mango, banana, lime, papaya and vegetables are being cultivated in salt‐ affected farms. Crop selection based on the irrigation water salinity, together with the adoption of appropriate salinity management strategies are crucial to sustain agricultural productivity under such conditions.  For all major crops, productivity decreased linearly with an increase in salinity. For sensitive crops such as mango, banana and most vegetables, the increase in irrigation water salinity from 1 to 3 dS/m reduced yield by as much as 50 percent.  There was an increase in all categories of farm animals from 1996 to 2009, despite the reduction in both the area and productivity of forages especially, the number of sheep increased by 68 percent from 2004 to 2005.

46 48

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 4. AGRICULTURAL MANAGEMENT TO IMPROVE PRODUCTION SYSTEMS IN AL BATINAH Soil and water salinity affects plant growth, resulting in lower crop yields and reduced agricultural production. In extreme cases, badly affected farms may need to be removed from agricultural production if management options to improve salinity are unsuccessful or not economic. Salinity may also affect the physical and chemical properties of soil, resulting in surface soil compaction and erosion. High levels of salts can dehydrate soil bacteria and fungi and reduce soil health, which is dependent on good microbial activity for the formation of organic matter and nutrient recycling. The breakdown in soil structure, together with the associated loss of plant cover, results in a greater exposure of the soil to erosion. The area of salt‐affected land is increasing because of irrigation practices and changed land use. Breeding varieties that tolerate soil salinity and yield well in salt‐affected soils, and employing crop management practices to counter salinity, have been proposed to maintain crop productivity.

4.1. Soil and water management There are two ways to manage saline soils. Firstly, salts can be moved below the root zone by applying more water than the plant needs – called the leaching requirement method. It is recommended that saline waters be applied more than the quantities necessary to meet the crop requirements. The exact amount will depend on the level of salinity of irrigation water, nature of soil, season and the crop (see Appendix 5). The second method combines the leaching requirement method with artificial drainage. Effective management of salt‐affected soils depends on adoption of site‐specific practices. Nevertheless, the following techniques generally help to minimize the negative effects.  Proper leveling of soil to prevent accumulation of salts in elevated areas  Deep ploughing to break any hard pan  Mulching and application of organic matter to improve physical properties of soil  Deep irrigation before sowing to migrate the salts from the soil surface  Higher seed rate to compensate for poor germination and priming for uniform stand establishment  Sowing on shoulders of ridges for better growth and yields  Salt scraping and piling away from cultivated areas.

4.2. Improvement in crop varieties and their management Plant breeding activities in Oman started in the form of introduction and selection of crop species in late 1960's. Nadaf et al. (2006) provided a detailed account of these and significant achievements are summarized below:

Grain crops such as wheat, barley and chickpea for food security and forages for livestock have been the priority in research. In almost three decades of research in field crops, more than 80 varieties have been found to be promising in 20 crop species from the concerted screening, evaluation and selection. These include 17 in wheat, 8 in barley, 8 in , 6 each in dry peas, Rhodes grass and alfalfa, 5 in chickpea, 3 each in sorghum, cowpea, sugarcane, fodder beet and 2 each in pearl millet, oats, mungbean, safflower and sunflower and one in sesame (Table 4.1).

47 49

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 4.1. List of elite genotypes of field crops selected and released from the breeding materials of international institutes.

Crops Elite genotypes / Varieties Wheat Mexipak, Sannine, WQS151, WQS160, WQS302, WQS 305, WQS 308, Jimah 1, Jimah 2, Jimah 101, Jimah 102, Jimah 103, Jimah 107, Jimah 110, Jimah 125, Jimah 132 Barley Beecher, Jimahh5, Jimah6, Jimah 51, Jimah 53, Jimah 54, Jimah 58, Jimah 98, Jimah 136 Sorghum Sugar drip, Honey drip, Fs x Dekalb 17 Maize Giza 2, Katamani 503, Hybrid 622, IRAT 8, Rumais Composite 1, Rumais Composite 2, Rumais Composite 3 Pearl Millet Super Mill, Feed Mill Oats Marloo, ARC‐1(Rumais1) Chickpea ILC237, Jimah 1, Jimah 2, Jimah 17, Jimah 18 Cowpea Jimah 2, Jimah3, Jimah 4 Dry peas ARC‐2 (Rumais2), ARC‐3 (Rumais3), ARC‐4 (Rumais4), ARC‐5 (Rumais5), ARC‐6 (Rumais6), ARC‐7 (Rumais7) Mungbean PS‐16, Sona, PDM 84‐13 Sesame Giza 23 Safflower A‐300, A‐1 Sunflower Turkey‐79, Miak Rhodes grass Callide, Katamboa, Samford, Elamba, Boma, Pioneer Alfalfa ADL 6725, CUF 101, Cundor, DK 187, Maxidor, Sequel, SW32AN Sugar cane CO‐419, CO‐658, CO‐678 Cotton MNH93, GIZA 72, BS1 Fodder beet Peramono, Petra, Anissa Atriplex species A. lentiformis, A canescens

Among perennial forages, Rhodes grass, buffel grass, signal grass and sudan grass were found promising yielding green fodder more than 100 t ha‐1 year‐1. Among perennial legumes, Siratro, Glycine and Leucaena were found to have the potential (>9 t ha‐1 per cut) to grow as supplementary to alfalfa. In alfalfa, however, none of the exotic varieties have excelled significantly in performance compared to local Interior or Batinah or Dhofari cultivars (8 to 10 t ha‐1 per cut) of green forage yield. In sugarcane, the cane yield has been increased from 47 to 110 t ha‐1. Fodder beet varieties Peramono, Petra and Anissa were identified as promising, with green fodder yields of more than 100 t ha‐1 under saline conditions (<5.0 dS/m), while Atriplex lentiformis and A. canescens were found to give more than 5 t ha‐1 year ‐1 of dry matter in salt affected waste lands.

In addition to field crops, introducing new varieties in different vegetables and fruit crops that are suitable for cultivation in Oman has also been pursued. Most of the varieties introduced in the vegetable crops such as tomato, cucumber, watermelon, muskmelon, pepper, cabbage, cauliflower etc. are hybrids of international companies. In fruit crops such as banana, mango,

48 50

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact citrus species (such as orange, lime, lemon, grapefruit), grapes, figs and guava seedlings, rootstocks, cuttings of exotic varieties have been introduced.

In 2001, the activities on improvement of three bread wheat land races/ cultivars such as Cooley, Missani, and Sarrya were initiated for high yield, early maturity, resistance against rust and smut diseases, and bread‐making quality. Four introduced and adopted bread wheat varieties (WQS 110, WQS 125, WQS 225, WQS 302) were used as male parents. A total of 12 crosses were made during winter 2002‐03 season. As a result of advancing generations in subsequent winter seasons the seed of 38 F5 elite families differing in their maturity are selected and being evaluated to release for farmers.

Similarly during winter 2004‐05 a local early barley cultivar namely Duraqui having salinity tolerance up to 6 dS/m and that matures in 75 days was subjected to crossing with 3 high yielding varieties Jimah‐51, Jimah‐136 and Jimah‐98 for improvement. During winter months of

December 2005 to February 2006, F1 seeds of three crosses were grown for harvest of F2 seed.

Combating salinity using novel crop species or indigenous rangeland species has been a recent approach in field crops research. While providing a detailed account of the salinity problem in the Sultanate, Al‐Rasbi (2009) summarized the research being undertaken by the Ministry of Agriculture (MAF), the University of Sultan Qaboos (SQU) and others since the early 1990s to alleviate the problem. These include:

 Study of the relative tolerance of some forestry species (Ziziphus spina‐christi, Acacia ampliceps, A. tortilis etc.) to salinity during germination  Identification of Citrus rootstocks (Cleaopatra mandarian and sour orange) tolerant to salinity  Study of the effect of different salinities on the growth and performance of some cereal and forage crops (e.g. wheat, barley, alfalfa, oats and Sudan grass)  Study of the effect of alternate irrigation with fresh and saline water on tomato which indicated that the average yield decreased by only 15 percent but achieved a 66 percent saving of fresh water at the same time.

In view of the need for the rational use of the scarce water resources owing to the serious water imbalance from extreme temperatures (high evapotranspiration) and low precipitation, and lack of information on crop water demand under local conditions, the Soil and Water Research Center (SWRC) at Al‐Rumais has been conducting studies on water‐use efficiency of various crops including Rhodes grass and vegetables (see MoA, Agricultural and Livestock Research Annual Reports, 2007‐09).

Summarizing the results of research related to salinity, Hussain (2005) and Ahmed et al. (2010) opined that although salinity problem has been consistently highlighted and emphasized in various surveys and integrated studies conducted in the country, the subject was never taken with the vigor and zeal it deserved. Lack of relevant information and data, and severe deficiencies in the salinity knowledge base were highlighted including the following:

 Scanty information and availability of data on soil salinity  Lack of monitoring soil salinity and well water quality changes

49 51

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

 No data available to predict the effect of groundwater on plant and soil  Leaching requirement to use saline water for different crops and in various soils are yet to be standardized  Management practices for salt affected lands were not generated  Exact salt tolerance of different crops/plants under local conditions is still unknown  No breeding work for evolution of salt‐tolerant varieties has been started  The reclamation technology for saline soils under Oman conditions has not been evolved  Halophytes of economic importance to be grown in highly saline soils supplied with saline water have not been identified.

The situation remained same even now and in addition to the above, the present study team (Working Group 2) experienced issues of data quality as different methods were used (especially standards/measures for crop yields) at different time for collecting the data which made the interpretation very difficult. Further endorsing the recommendation of Ahmed at al. (2010) that biosaline agriculture in terms of development and introduction of new crops and salt‐tolerant varieties of existing crops should be given priority along with the water focused solutions, we also suggest establishing data collection guidelines to provide a unified approach to data collection to better facilitate the consolidation of findings and to allow the data to be more useful to analyze trends, for scientific research, and as information for decision‐makers.

4.3. Crop diversification and alternate production systems In salt affected areas, diversification of production systems with crops more tolerant to salinity than the existing ones can be an important adaptation strategy to alleviate the negative effects of salinity and sustain farm productivity. Sustainable production practices involve a variety of approaches. Despite the site‐specific and individual nature of sustainable agriculture, several general principles can be applied to help growers select appropriate management practices including selection of species and varieties that are well suited to the site and to conditions on the farm and diversification of crops and cropping systems, and cultural practices to enhance the biological and economic stability of the farm. Including livestock in the farming system increases the complexity of biological and economic relationships.

To diversify crops, reliable information will be required to predict yields of the alternative crops in response to various levels of salinity in the root‐zone. Based on extensive literature search, Maas and Hoffman (1977) concluded that crop yield as a function of the average root zone salinity could be described reasonably well with a piecewise linear response function characterized by a salinity threshold value below which the yield is unaffected by soil salinity, and above which yield decreases linearly with salinity. However, as discussed under Section 3.3, Steppuhn et al. (2005) after re‐reviewing over 200 data sets from experiments around the world found that these thresholds do not exist (except for some halophytes) and instead there is an ever decreasing loss in production with increasing salinity. This implies that for every crop, an acceptable level of irrigation water and root‐zone salinity exists in relation to the margin of returns resulting from the irrigation per se and with limited increases in salinity of water, the positive effects will significantly outweigh the negative influence associated with an increased salinity.

50 52

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact Crop suitability – factors affecting choice of crops The Table 4.2 below lists the major crops grown in Oman according to their cultivated area in 2010 and their tolerance or sensitivity to salinity. In farms affected by salinity, selecting tolerant crops with low water requirements would not only contribute to sustain agricultural productivity but also enhance water productivity, contributing to saving fresh water resources that are otherwise used for irrigation. Therefore, the water requirements for the crops currently grown in Oman are also presented in Table 4.2, to help in selecting appropriate crops to match the salinity of irrigation water combined with low water requirements.

Table 4.2. Water requirements and salinity tolerance of some major crops cultivated in Oman (Source: EAD/ICBA, 2010). Crops Water consumption Salinity tolerance* (m3 ha‐1) Range Mean Crop tolerance Vegetables/Fruits Tomato 3,100‐7,400 5,557 Moderately sensitive Cucumber 1,800‐5,000 3,242 Moderately sensitive Pepper 2,000‐8,000 6,067 Moderately sensitive Musk melon 2,300‐8,900 6,225 Tolerant Squash 2,300‐3,000 2,500 Moderately tolerant Eggplant ‐ 2,400 Moderately sensitive Cauliflower 1,000‐3,400 2,133 Moderately sensitive Cabbage 1,600‐3,600 2,300 Moderately sensitive Watermelon 4,000‐5,500 5,025 Moderately sensitive Okra 3,600‐9,900 8,514 Sensitive Onion 2,500‐8,400 5,429 Sensitive Lettuce 2,000 2,000 Moderately sensitive Fruit trees Palm tree ‐ 14,800 Tolerant Lime ‐ 10,200 Sensitive Lemon ‐ 14,800 Sensitive Grape ‐ 9,400 Sensitive Orange ‐ 10,200 Sensitive Mango ‐ 9,500 Sensitive Guava ‐ 9,500 ‐ Jujube ‐ ‐ Moderately tolerant Pomegranate ‐ 9,500 Moderately tolerant Banana ‐ 17,200 Sensitive Green fodder Alfalfa ‐ 15,700 Moderately sensitive Rhodes grass 15,000 Moderately tolerant Other crops Corn 5,000‐8,000 ‐ Moderately sensitive Wheat 4,500‐6,000 ‐ Moderately tolerant Barley 4,500‐6,000 ‐ Moderately tolerant Potato 5,000‐7,000 ‐ Moderately sensitive Cowpea ‐ 2,400 Moderately tolerant * Sensitive (ECe: <2 dS/m); Moderately sensitive (ECe: 2‐4 dS/m); Moderately tolerant (ECe:4‐6 dS/m); Tolerant (ECe: >6dS/m).

51 53

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Crops such as Rhodes grass require large amounts of water (approximately 15,000 m3 ha‐1 yr‐1). It is possible to replace these with alternative forages that require less water. In this respect, native grasses like buffel grass (Cenchrus ciliaris) and tuman (Pennisetum divisum) appear to have excellent potential. These grasses survive with very little water and are well‐adapted to the harsh desert environment. Recent studies have shown that buffel grass has significantly lower water requirements than Rhodes grass (Osman et al., 2008) and its nutritional quality is similar (Peacock et al., 2003).

The Arabian Peninsula Regional Program (APRP) of the International Center Agricultural Research in the Dry Areas (ICARDA) in collaboration with the National Agricultural Research Systems (NARS) in the Arabian Peninsula countries including Oman is promoting integrated production systems based on indigenous forage species with high water use efficiency. As part of this initiative, 13 farmers have adopted buffel grass over a total area of 3.5 feddans (1.5 ha) by 2009 (see ICARDA/APRP, 2010). Further development of these forages and their large‐scale adoption nevertheless requires more research, followed by extension work to translate the research results into practical recommendations. A ‘forage improvement program’, with a team of breeders, agronomists and extension specialists, is therefore recommended. In addition to the crops already being cultivated, alternative crops with adaptation to the Oman environment and with low water requirements are listed in Table 4.3.

Table 4.3. New crops with potential for introduction in Oman. The crop thresholds values are from Maas and Hoffman (1977) and C50 values from Steppuhn et al. (2005).

Crop Use Thres‐ C50 Water Tolerance hold demand (ECe) (ETc in mm)* Asparagus Vegetable (Perennial) 4.1 28.5 1,473 Tolerant Buffel grass Forage (Perennial) 4.0 ‐ 1,443 Moderately tolerant Canola Forage/Oil 11.0 7.1‐14.4 401 Moderately tolerant Cowpea Forage/Vegetable/Seed 4.9 6.7‐8.7 462 Moderately tolerant Fodder beet Forage 7.0 9.1 433 Tolerant Guar Forage/Vegetable/Seed 8.8 11.3 354 Tolerant Mustard Vegetable/Oil ‐ ‐ 489 Moderately tolerant Pearl millet Forage/Seed 4.0 ‐ 301 Moderately tolerant Pigeonpea Forage/Vegetable/seed ‐ ‐ 510 Sensitive Purslane Vegetable 6.3 11.1 ‐ Tolerant Quinoa Seed/Forage ‐ ‐ 255 Tolerant Safflower Forage/Oil 4.3 ‐ 653 Moderately tolerant Sesbania Forage 2.3 9.1 582 Moderately tolerant Spinach Vegetable ‐ 8.2 Moderately tolerant Sunflower Oil/Ornamental 4.8 14.3 409 Moderately tolerant Triticale Forage/Seed 6.1 25.5 449 Moderately tolerant

* Estimates based on ETo values at ICBA Research Station and Kc values from Allen et al. (1998).

52 54

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Managing salinity would require different approaches, both on short‐ and long term. The short‐ term approach would mainly be related to the mitigation of the low‐salinity agricultural farms, where existing crops could be grown through improved management practices, including:

1. Selection and improvement of more drought‐ and salt‐tolerant genotypes. 2. Improved and efficient water/irrigation management. 3. Soil reclamation/improvement through mulching and other management.

The saline areas that would fall under the above category would be in the range of ECw 2‐10 dS/m or 1,400‐7,000 ppm (~ ECe 3.5‐15 dS/m or 2,500‐10,000 ppm). For areas that have higher salinity (more than ECw 10 dS/m or 7,000 ppm (ECe 15 dS/m or 10,000 ppm), adaptation strategies need to be designed, mainly in terms of changing crops and cropping patterns, introduction of forage‐based production system and others (referred to as Alternative Production Systems). The Table 4.4 provides recommendations for crop selection to overcome salinity hazards.

53 55

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 4.4. Recommendations for crop selection to overcome salinity hazards (Source: EAD/ICBA, 2010).

Salinity Recommendations

ECw (TDS) < 0.7 dS/m Full yield potential should be achievable with nearly all crops. (< 500 mg TDS/l) <0.7 ‐ 4.0 dS/m With good management, most fruits and vegetables currently being (500‐2800 mg grown can be produced. Full yield potential is still possible but care TDS/L) must be taken to achieve the required leaching fraction in order to maintain soil salinity within the tolerance of the crops. >4.0 dS/m The water might still be usable but it’s use may need to be restricted (>2800 mg TDS/L) to more permeable soils, where high leaching fractions are more easily achieved. If the crops are salt‐sensitive (e.g. fruits and vegetables), the solutions are: a. Increasing leaching to satisfy a leaching requirement greater than 0.25 to 0.30 (negative points: excessive amount of water is required). b. Selecting irrigation system with uniform application, high efficiency of irrigation (drip irrigation and mini‐sprinklers). c. Scheduling of irrigation: more frequent irrigation with micro‐ irrigation systems to enable maintenance of lower levels of salinity in the plant root zone. d. Drainage which allows for the leaching of excess salts (in combination with irrigation scheduling). e. Soil conditioners ‐ though not recommended because of high price and low efficiency in certain periods/conditions. If there are limitation to execute the above solutions, consideration must be given changing to a more tolerant variety of the same crop, or to other relatively tolerant crop(s) that will require less leaching to control salts within crop tolerance levels. > 10 dS/m Selection of alternative crops with much higher levels of tolerance to (>7000 mg TDS/L) salinity, i.e. those with the ability to absorb high amounts of salts, i.e. moving to alternate production systems by: a. Change in crops and/or cropping pattern b. Forage production c. Land/Soil management d. Integrated crop‐livestock systems e. Tree‐based, bio‐energy, C‐sequestration, bio‐remediating production systems Appropriate irrigation and drainage management should go hand in hand with the above to maintain soil salinity within the limit.

4.4. Protected agriculture The limited availability of fresh water resources in Oman makes it necessary to adopt strategies that help in the reduction of water use in agriculture or make the most efficient use of water. In

54 56

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact this respect, protected agriculture (PA), particularly for growing high value crops such as vegetables appears to have significant potential. PA is a challenging task on technical as well as economic accounts. Higher technical knowledge is required to manage plant nutrient requirements, choose the right kind of cultivar and irrigation scheduling, maintain temperature and humidity and take proper plant protection measures. ICARDA has previously used this technology with promising results in Yemen and Afghanistan, where water efficient techniques were successfully introduced to small‐holder farmers. Besides improved water‐use efficiency, other benefits of PA include: Increased production and availability of vegetables to consumers, creation of more employment and export opportunities and regular income to the farmers. In Yemen, cucumber productivity was 17‐fold greater under PA, while tomato reached 12‐times its productivity as compared to open fields. Protected agriculture with its associated growing systems can also minimize environmental degradation in a number of ways compared with field crop production. For instance, it can:

1. significantly reduce the amount of fertilizers utilized in growing the plants, 2. reduce and possibly eliminate the potential contamination of groundwater by fertilizers, 3. eliminate or minimize the use of toxic pesticides through the adoption of integrated plant protection program and use of biological control methods.

Currently, PA in Oman covers a total area of 42 ha, mostly in Al Batinah Governorates. There are three main types of PA structures used in the Sultanate: single‐span greenhouses, double‐span greenhouses, and screen‐houses. The single span greenhouse (usually 9 × 40 m), covered with a double layer of polyethylene sheets, with evaporative cooling system and a single door is the one most used in the Sultanate.

In Oman, research into protected agriculture began in 1992 with the screening and evaluation of cucumber, tomato and sweet pepper in plastic houses. Initial trials at the Agricultural Research Center at Rumais revealed a number of constraints (see Sidahmed et al. 1998) that included:  Designing ‐ the single‐span plastic house with evaporative cooling system and a single door that allows for insect infestation.  High cost of structural material.  Lack of capacity for integrated pest management.  Build up of pests and soilborne pathogens and soil degradation due to intensive cultivation.  Excessive residues of toxic chemicals in the produce (cucumber).  Shortage of qualified personnel and trained technicians.

In view of the above, the following recommendations were made to alleviate these constraints.  The structure of the greenhouses in use needs to be improved for better environmental control and ventilation and to reduce running costs (electricity and water).  Multi‐door entrances to make them less accessible to insects.  Strategies for integrated pest management.  Improved cultural and husbandry practices, such as fertigation and water‐use efficiency.  Sterilization of soils and crop rotation.  Defining safe levels of toxic residues.  Training of Personnel involved in protected‐agriculture.  Allocation of budget for research.  Need for control and monitoring equipment.

55 57

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Some of the issues discussed above are being addressed in the collaborative project "Technology Transfer to Enhance Rural Livelihood and Natural Resource Management in the Arabian Peninsula", Protected agriculture for high value crops between ICARDA and Protected agriculture allows growers to produce more of the high value the Ministry of vegetable crops such as tomatoes, peppers, cucumbers, strawberries and Agriculture & Fisheries watermelons – with higher plant densities – on a year‐round basis. Pilot (MAF). One of the trials in Oman have shown boosting of yields by 10 times or more over major outcomes of this field‐grown production. For instance, in cucumber, in pilot trials, growing project is the shift in two crops per year under greenhouse conditions, maximum yields of up to 10 tonnes (which amounts to 277 t/h/year, considering that each PA towards soilless greenhouse is close to 360 m2) were reported. One farmer growing four (hydroponics) cultures crops obtained a total of 19.75 t/greenhouse/year (i.e. ~550 t/ha/yr) with integrated produ‐ (ICARDA/APRP, 2010), but yields even higher than these were reportedly ction and protection attained indicating the significant potential of protected agriculture for management (IPPM) Oman. However, it should be recognized that protected culture is very for high quality cash capital intensive, even at the lowest technology level. The operating costs crops. Application of are also equally expensive ‐ a one hectare greenhouse may equal the cost IPPM techniques resul‐ of 40 hectares of open field agriculture plus the cost of support facilities ted in good yields, and equipment. Thus, growers investing in greenhouse technology will reduced spray of require substantially higher yields and higher prices to compensate for higher production costs per metric ton. insecticides and effici‐ ent water productivity It should also be borne in mind that any production system is compared to control unsustainable if agricultural practices impose negative externalities or greenhouses. For create environmental degradation. This is especially true in the context of instance, yield of 10.3 Oman where the greenhouses currently in use require huge amounts of kg m‐2 and water water for the cooling system, offsetting any reduction achieved for crop productivity of cucum‐ growth. Given that most crops of high value grown under protected ber were 72 kg m‐3 agriculture are highly perishable, the process of marketing and were reported in distribution can be another key factor in determining the success of the system. Over‐production and an unorganized market system could in fact cucumber under soil‐ result in huge post‐harvest losses, requiring additional investment and less production sys‐ operating costs in terms of building cold storage facilities and their tems with pilot maintenance. Protected agriculture could also face the greatest growers (ICARDA/ competition from imported produce both greenhouse and field grown, APRP, 2010). The particularly from countries which have more favorable climatic hydroponics system conditions. Therefore, a realistic assessment of the true benefits of although doesn't rely protected agriculture to Oman is only possible in an analysis that includes on soil quality of the the costs of all the negative externalities, in addition to the expenses of farm, it still needs countering long‐term degradation of natural resources. freshwater for crop production. While a number of farmers are adopting the technique, some have even installed small desalination plants to facilitate soilless production systems.

However, it is pertinent to add that that the overall economics of production under protected agriculture should be thoroughly tested and evaluated as also advocated by Sidahmed et al. (1998). This is especially true because water, both in quality and quantity, is one of the major limiting factors for the development of agriculture in general and PA in particular. In salt‐ affected areas, successful production of high‐value crops from greenhouses requires good‐

56 58

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact quality water that in many cases is produced from desalination units at a high cost. More importantly, the greenhouses are based on fan‐and‐pad cooling systems which require large quantities of relatively good quality water for cooling. The fan‐and‐pad cooling systems are sensitive to sand storms and direct solar radiation and the pads tend to clog with salt and sand. Further, high light intensity and temperature, combined with high relative humidity, characterizes the climate in Oman and the PA structures that are widely used in the country are those that have been developed to suit cool‐weather countries where the environmental conditions are very different. Thus, for sustainability and long‐term economic viability, greater attention should be given to identifying the most suitable climatic zones with favorable growing conditions (economically), ventilation, cooling systems and the covering maternal. While there is need to increase production efficiency through structural modifications to suit Oman’s environmental conditions including the possible use brackish or seawater for cooling, the economics of production ‐ especially during the summer months (April‐October) should be carefully evaluated to make suitable recommendations for profitable use of the PA technology.

4.5. Integrated farming systems (Crop‐livestock integration) Native rangeland vegetation especially on Al Batinah plains, in wadis, Dhofar mountains and Al‐ Jabel Al‐Akhdar used to provide a large proportion of the feed needs of ruminants in the past. However, due to increase in small‐ruminant numbers in recent years, the contribution of natural grazing as a proportion of total feed resources has declined. Not only are rangeland resources insufficient to meet the current demand, the absolute level of feed resources is in decline due to overgrazing, rangeland degradation and increase in salinity. In salt‐affected areas where cultivation of staple forages (Rhodes grass, sorghum and some perennial legumes such as alfalfa) becomes uneconomical, alternative production systems based on highly salt‐tolerant forages provide an opportunity to sustain farm productivity and meet the increased demand for animal feed and integrating livestock to further minimize risk under adverse conditions. In an integrated system, crops and livestock interact to create a synergy, allowing the maximum, as well as the best use of available resources (Figure 4.1). It helps increase profits by reducing production costs, especially chemical fertilizers. The waste products of one component serve as a resource for the other. For example, manure is used to enhance crop production; crop residues and by‐products feed the animals, supplementing inadequate feed supplies, thus contributing to improved animal nutrition and productivity (see IFAD, 2010).

Figure 4.1. Key elements of integrated crop‐livestock production system (Adopted from IFAD, 2010).

57 59

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

The overall benefits of crop‐livestock integration include:  Agronomic – through the retrieval and maintenance of the soil productive capacity helping to improve and conserve the productive capacities of soils, with physical, chemical and biological soil recuperation.  Economic – through product diversification and higher yields and quality at less cost.  Ecological – through reduction in chemical fertilizers and ground water pollution and greater soil water storage capacity.  Socio‐economic – through providing diversified income sources, thus guaranteeing a buffer against price and climate fluctuations. While a high integration of crops and livestock is often considered as a step forward, farmers need to have sufficient access to knowledge, assets and inputs to manage this system in a way that is economically and environmentally sustainable over the long term (IFAD, 2010).

4.6. Main observations  Major deficiencies exist in the salinity knowledge base, especially in relation to crop management and productivity in salt‐affected areas which have hampered in the current project, the realistic assessment of the problem.  Establishing data collection guidelines to provide a unified approach to data collection is important to allow for trend analysis and scientific research, and to serve as information for decision‐makers.  Efforts in the past to monitor salinity, and research to alleviate the effects have been inadequate vis‐à‐vis the extent and severity of the problem.  Managing salinity requires different approaches ‐ both mitigation and adaptation depending on the severity of the problem and targeted production systems and may include: o Improved and efficient water/irrigation and soil management. o Soil reclamation/improvement through mulching and other management practices. o Improved crop management. o Selection and improvement of more salt‐tolerant genotypes. o Changing crops and cropping patterns, introduction of forage‐based production system with livestock integration. o Educating/capacity building of farmers.  Protected Agriculture has considerable potential. However, for sustainability and long‐term economic viability, greater attention should be given to the selection of most favorable sites and structural improvements including ventilation, cooling systems and the covering maternal for profitable use of the technology.

58 60

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 5. SHORT‐AND LONG‐TERM ADAPTABILITY OF IMPROVED

CROPS FOR SUSTAINABLE YIELD PRODUCTION

Although land capability in Oman is affected by a range of soil factors, the economic value of intervening to improve agricultural productivity in Oman will depend primarily on the salinity of the groundwater (see Figure 5.1). This figure recognizes five important points:

1. Groundwater salinity is a continuum – extending from non‐saline to highly saline levels.

2. Salinity of the groundwater is the core parameter affecting land capability in Oman. It is relatively easily measured and, unlike soil salinity, is not likely to be highly spatially variable at the “within field” scale.

3. The profitability of existing farming systems decreases with increasing groundwater salinity. The value to farmers of intervening to improve productivity will be greatest at low salinity and these benefits will decrease as groundwater salinity increases. Thus, Naifer et al. (2011) estimated the economic losses incurred by farmers due to salinity by comparing the profitability of the medium and high salinity farms to the low salinity farm’s gross margin. The results showed that when salinity increases from low (<2.5 dS/m) to medium level (7.5 dS/m), the damage would be US$ 1,604 ha‐1 and if salinity increases from medium to high (>7.5 dS/m) level, the damage would be US$ 2,748 ha‐1. Introduction of salt‐tolerant crops in the cropping systems show that the improvement in gross margin is substantial thus attractive enough for medium salinity farmers to adopt the new crops and/or varieties to mitigate the effect of water salinity. However, in the high salinity farms the gross margin improvement is too low to encourage farmers to adopt salinity tolerant crop varieties.

4. Implementing new strategies by farmers will have the greatest benefits relative to costs at lower salinity and as salinity increases, there will be a point at which the costs of implementing new strategies becomes so costly (relative to benefit) that the systems become uneconomic by themselves. In this situation, if the Government wants farmers to implement biosaline agricultural systems, then subsidies will be required to encourage farmer adoption.

5. At low groundwater salinities, the optimal solution will be to improve the current agricultural system; at higher groundwater salinities, the optimal solution will be to adopt biosaline approaches (better germplasm and management); at intermediate groundwater salinities, the optimal solution will be to adopt a mixed approach.

59 61

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Figure 5.1. Conceptual framework of the value of intervention compared with the “Business as usual ”, and the relationship of this to the severity of salinity (based on Masters et al., 2006). The type of incentives required to achieve change in the farming system is indicated in the upper box above the graph. The type of agricultural system likely to be optimal is indicated in the lower box above the graph.

5.1. Scenarios based on improving current agricultural systems The yield of agricultural crops in non‐saline soils in Oman is hugely variable. There are large areas of cropped land in Oman where salinity is not an acute problem. In Al Batinah and Salalah surveys about 60 percent of farms had groundwater with salinities (ECw) values of less than 5 dS/m. However, even without salinity, the productivity of much of this land was still low. We took the OSS data set and filtered it for farms with ECw values less than 3 dS/m (a clearly non‐ saline threshold). We then searched the remaining data (254 farm records) to find the highest yield for 5 staple crops – dates, alfalfa, mango, banana and lemon. We refer to this maximum yield as “best practice”. Figure 5.2 shows the distribution of yields (as a percent of “best practice”) for these five staple crops in Al Batinah Governorates. For all of these crops, yields relative to “best practice” were low. Dates were the best‐grown crop with the median farm producing yields of 25 percent of best practice; in contrast, with the other four crops, the median farm had yields of 2‐6 percent of best practicce.

60 62

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

100 Dates 90 Alfalfa 80 Mango Banana 70

farms Lemon

of 60 class) 50 in

(% frequency

40

30

Relative 20

10

0

Yield as percent of maximum in survey Figure 5.2. Relative frequency of non‐saline farms with different percentages of maximum yield (Source: OSS Batinah Survey, 2010). Frequency distributions were determined using data where ECw values were less than 3 dS/m. The number of farms remaining in the filtered dataset were: 233 farms (dates), 100 farms (alfalfa), 91 farms (mango), 79 farms (banana) and 63 farms (lemon).

In our final analysis of the OSS data, we also asked the question about the transferability of farmer competence – that is whether farmers that were highly competent in the growth of one crop were also competent in the growth of another. To do this, we took the 254 farm records from the OSS survey and sorted all farms from highest yields of a given crop to lowest yields of that crop. These farms were then ranked with a number from highest to lowest. This process was then repeated for each of the main crops. We then determined if these rankings were correlated. The results of this exercise for the four major crops of Al Batinah survey are indicated in Table 5.1. Table 5.1. Correlations between rankings of the ability of farmers growing different combinations of crops with 0‐3 dS/m groundwater. A. Significance of correlations between rankings. Crop Alfalfa Mango Banana Lemon Date *** * * NS Alfalfa NS * NS Mango NS NS Banana NS Levels of significance are: *** P <0.001; ** P < 0.01; * P<0.05; NS not significant.

61 63

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

B. Number of farms growing both crops. Crop Alfalfa Mango Banana Lemon Date 96 89 77 61 Alfalfa 44 30 27 Mango 38 34 Banana 29 The analysis of Table 5.1 supports the view that farmers who are competent in the growth of one crop are also competent in the growth of another. The correlations between farmer rankings with different combinations of crops is clearest in the case of farmers who grow both dates and alfalfa (P<0.001; Figure 5.3). Although there were exceptions, many farmers that were competent in the growth of dates were also competent in the growth of alfalfa. The significance of this correlation indicates that farmer competence carries across different crops, and it suggests that building farmer skills may have benefits for the yields of more than one crop.

100 y = 0.238x + 21.20 80 R² = 0.375 farms

of 60

rankings 40 ‐

20 Alfalfa

0 0 50 100 150 200 250 Dates ‐ ranking of farms

Figure 5.3. Rankings of farms for yield of dates against rankings of farms for yield of alfalfa. Source of data: OSS survey filtered for farms with ECw < 3 dS/m.

5.2. Technical and economic impacts of alleviating salinity by introducing other production systems One of the clear conclusions of the OSS is that there are many farms in Oman where salinity is an important problem. In Al Batinah and Salalah surveys, 30 and 40 percent of farms respectively had groundwater with salinities (ECw) values of more than 5 dS/m. At this level and higher, salinity would be a challenge to the growth of high‐yielding conventional crops. There are two critical aspects that need to be focused on in the development of new production systems for land with saline groundwater in Oman:  Plants vary in salt tolerance. It may therefore be possible to build new agricultural systems based around non‐traditional crops. The choice of plant genotype is therefore critical.

62 64

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

 Plant growth in saline soils is controlled by the salinity of the soil solution; which is controlled by the salinity of the irrigation water, the leaching fraction and the irrigation frequency. Salt and water management in the soil profile is therefore critical. Given this it is suggested that a project be established that involves partnerships between the Ministry of Agriculture, SQU, relevant international organizations (like ICBA) and farmer groups, with the following objectives.  Ensure that reliable relationships are available for the major crops grown in Oman relating crop yield to irrigation water salinity and irrigation practice.  Assess improved salt tolerant germplasm to be used for establishing on‐farm demonstrations (crops and forages) in salt‐affected areas of Oman.  Determine the best soil management, agronomic and irrigation practices to manage salinity in root zone and therefore increase productivity.

Relationships between crop yield, irrigation water salinity and irrigation practice One of the frustrations in the current work is that it has not been possible to demonstrate the link between crop yields under best practice conditions, and irrigation water salinity, soil salinity and irrigation management (frequency and amount). This is critical foundation information. The Government of Oman and the Ministry of Agriculture will not be in a position to encourage farmers to change from inefficient to efficient irrigation practices if it can’t develop data sets that show that such transitions are possible with increasing productivity. We recommend that this capability be established as a high priority.

 Improved salt tolerant germplasm. Comparisons need to be made between the growth and productivity of a range of salt tolerant germplasm of the important crops to Oman and current cultivars. The advanced material would be provided by ICBA or other international partners as required. This work would also include the testing of a range of halophyte species suitable for economically‐feasible fodder and biomas production.

 Improved salt and water management. As discussed earlier, the critical factor driving plant growth on saltland is the salinity of the soil solution, which is affected by the salinity of the groundwater, the leaching fraction and the irrigation schedule. For a selected group of model crops it is recommended that research be conducted into how different combinations of irrigation water salinity, water application rate, frequency of application, and soil surface mulching treatments affect the salinity of the soil solution in the root‐zone and growth. This work would be used to develop decision support tools for farmers so that water could be used most efficiently to increase yield.

5.3. Experience from other countries This section addresses three critical issues that arise from the international experience in farming systems research and biosaline agriculture.

63 65

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 5.3.1. Biosaline agriculture is now a recognized way of improving production with saline resources Selected examples: General situation. With few exceptions (see Pakistan on page 65), the introduction of biosaline agricultural systems does not change the salinity of the land or water resource affected, but does provide a means of achieving production from saline land and/or water resources (Barrett‐ Lennard, 2002). In the mid‐1980s, 18 countries were recognized as having adopted some form of saltland revegetation (Barrett‐Lennard et al. 1986). ICBA’s experience. Selection and use of genetic variation already present in existing crops and developing halophytes as alternative crops have been the two main approaches adopted by the Center to improve productivity of salt‐affected lands. Through the efforts undertaken by ICBA in partnership with the National Agricultural Systems (NARS) including Oman in the Middle‐East and North Africa region, measurable advances were made in terms of identifying suitable forage genotypes of annual (barley, pearl millet, sorghum, triticale, fodder beet and forage Brassica), cash crops (safflower and sunflower), and perennial grass (Buffel grass, Sporobolus, Distichlis) and shrub species (Sesbania, Atriplex and Acacia). The combinations of summer and winter annual forages and perennial grass and shrub forages, along with proper management packages, have demonstrated to improve farm productivity and provide options for crop diversification to the farmers. Australia. Southern Australia has an extensive secondary salinity problem caused by: (a) the replacement of deep‐rooted perennial native vegetation with shallow rooted annual species, and (b) a consequent rise in water tables that brings salt stored deep in the profile to the soil surface. About 5.7 million ha are presently regarded as being at risk from salinity because of shallow water tables and this figure is expected to grow to 17 million ha by the year 2050 (National Land and Water Resources Audit, 2001). One solution to landscape salinity lies in the reintegration of trees and other perennial species back into groundwater recharge areas with the aim of returning hydrological function to a condition that mimics that of the original landscape (Hatton and Nulsen, 1999). Although some perennial options are available, widespread farmer uptake of most of these has been poor because of their low profitability. The most acceptable solution for this land has therefore been through revegetation with salt tolerant trees (Marcar et al., 1995) or fodder shrubs and grasses (Barrett‐Lennard et al. 2003). Further information about the Australian programs is provided in Appendix 6. Pakistan. Pakistan has had a substantial commitment to the development of saline agriculture since the 1980s, with key nodes of research in Karachi and Faisalabad. Research has focused on the development of salt tolerant crops, forages and trees (Ahmad and Ismail, 1996, Qureshi and Barrett‐Lennard, 1998). One of the unique features of the Pakistani experience has been the use of some of Pakistan’s fine textured soils becoming saline because of a sodicity problem; with sodic irrigation water unable to leach into the soil profile and salts therefore accumulate at the soil surface. However, with the growth of the salt/waterlogging tolerant species Leptochloa fusca (kallar grass), the intensely sodic/alkaline soils are slightly acidified, hydraulic conductivity in the soil is restored, and the soils became non‐saline again. This is the only example (of which we are aware), where the adoption of biosaline agriculture without drainage has reversed a salinity problem. Iraq. Iraq is a good example of a country that had a viable saline research program, which needed restarting. Since 2010, ICARDA has been collaborating with partners in Australia and

64 66

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

ICBA to deliver a research project focused at three scales in Iraq: (a) the catchment scale, (b) the irrigation district scale; and (c) the farm scale. Although the research is made difficult by the unstable political situation in the country, the international team has been able to collaborate with Iraqi researchers on the ground, and salt‐tolerant plants from ICBA are being tested in two saline landscapes. A mirror trial conducted in Syria has pointed to the importance of the interaction between salinity and boron toxicity on the relative growth of wheat and barley.

5.3.2. Integrated farming systems approaches are required to maximize plant yield The principle innovation of the “Green Revolution” across the world was the way in which farming systems approaches were used to increase crop yields many‐fold. These systems comprised combinations of the right crop genotype, the right watering regime, the right fertilizer strategy and the right method of control of weeds, pests and diseases. Naifer et al. (2011) estimated the economic losses incurred by farmers due to salinity by comparing the profitability of the medium and high salinity farms to the low salinity farm’s gross margin. Results showed that when salinity increases from low salinity to medium salinity level the damage is US$ 1,604 ha‐1 and US$ 2,748 ha‐1 if it increases from medium salinity to high salinity level. Introduction of salt‐tolerant crops in the cropping systems show that the improvement in gross margin is substantial, thus attractive enough for medium salinity farmers to adopt the new crops and/or varieties to mitigate the effect of water salinity. However, in the high salinity farms the gross margin improvement is too low to encourage farmers to adopt salinity tolerant crop varieties.

5.3.3. Extension gaps between farmers and researchers can be overcome using participatory approaches In general farmers are practical people for whom “seeing is believing”. They often have a distrust of researchers but will believe the extension messages of fellow‐farmers. Building participatory research programs in which research is conducted as collaboration between farmer groups and researchers can be a very effective way of overcoming these gaps. However, the sustainability of farmer groups does depend on farmer leadership; we may therefore need to accept that farmer groups have a finite life, and “enjoy the ride” in the partnership while it lasts. Examples:  Sustainable Grazing on Saline Lands Initiative (Australia). Between 2002 and 2007, the Cooperative Research Centre for Dryland Salinity and two industry organizations (Australian Wool Innovation Ltd and the Meat and Livestock Corporation) invested in a major program called Sustainable Grazing of Saline Lands (SGSL). Building on the historical work of pioneer Australian researchers, this project built a national coalition of saltland agronomists and livestock researchers to work with 120 existing farmer groups around Australia to develop grazing solutions for saltland (Barrett‐Lennard et al., 2005). The project had used participatory research principles so that farmers could trial saline agricultural solutions on their own fields, and also conducted on the ground research into the factors affecting saltland productivity for a range of saltland pasture.  The Saltland Pastures Association (Western Australia) and Salinity Solutions (South Australia). Although Australia has a substantial salinity problem, for a variety of political and economic issues during the late 1990s, research into saline agriculture virtually ceased in

65 67

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Australia. The “Saltland Pastures Association and Salinity Solutions” catalyzed extraordinary change in farmer adoption of saline agriculture in their communities in Western Australia and South Australia respectively.

5.4. Reducing the yield gap The OSS Batinah survey revealed that the yield of agricultural crops in non‐saline soils in Oman is highly variable and the productivity was very low even under non‐saline conditions. For example, in farms with water salinity of <3 dS/m, date palm yields ranged from 0.1 tonnes to 8.8 tonnes per feddan, with over 55 percent of the farms having only a third of the maximum recorded yield. Similarly, the yields of the leading 10 percent of farmers were 34‐times higher than the yields of the lowest 10 percent of farmers. In terms of overall agricultural performance, although Oman does reasonably well in comparison to other countries in the MENA region, the aggregate average yield falls far below the globally accepted yield under irrigated medium‐input conditions, by as much as 27%.

5.4.1. How big are global yield gaps? Average farm yields in a region or country are inevitably smaller than yield potential, sometimes significantly so, because achieving yield potential requires near perfect management of crop and soil factors that influence plant growth and development throughout the crop’s growth cycle (Lobell et al. 2009). Although a few superior farmers may come close to this state, it is neither profitable nor feasible for a large population of farmers to do so. Therefore, monitoring crop yields is crucial and as the average farm yields appear to fall off from historical yield trends, it is important to determine if this is caused by the diminishing size of the exploitable yield gap or by other factors such as soil degradation, pollution, or climate change.

A survey of the literature on major crops such as wheat, rice, and maize cropping systems reveals a wide range of estimated yield gaps throughout the world. Lobell et al. (2009) estimate that yield gap values from major cropping systems of the world range between 20% and 80%. For example, for tropical maize in Africa, average yields are commonly less than 20% of yield potential. In contrast, average yields in irrigated wheat systems in northwest India reach up to 80% of potential.

Assessment of potential yield and the yield gap between potential and actual yield is essential before any investment for improving crop production for a location is made. A multitude of factors ranging from lack of agricultural service provision (extension), lack of knowledge among farmers, insufficient adaptation of crop varieties to local conditions or misalignment of researchers’ and farmers’ objectives determines the width of a yield gap as illustrated in Figure 5.4 below. It can be seen that while the average maize yield in Illinois has closely followed the growth in yield potential at the state’s experiment stations, the picture for Mexico strongly contrasts that. Mexican average yields since the early 1990s not only remained low but the yield gap also has widened. Crop yield gap dynamics for most developing countries will be closer to the Mexican than to the Illinoisan picture.

66 68

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Figure 5.4: Maize yield gaps for Illinois and Mexico (Source: Lobell et al. 2009)

The list of factors that commonly affect crop growth and yields in farmers’ fields is long and varied. These factors include stresses that are biotic in nature and others that are mainly abiotic, factors that are easy to measure and some that are difficult to detect, factors that relate mainly to management and others to soil properties, as well as interactions among these various factors. The challenge to understand yield gaps for any given farming syystem is to identify among the many possible explanations for yield losses the few that have the greatest influence and, if possible, to quantify the gains that could be realized if these constraints were removed. The relationships between true (model simulated) yield potential, experimental yields, maximum farmer yields, and average farmer yields are shown in Figure 5.5. In very intensively managed systems where farmers attempt to avoid all nutrient, pest, and disease stresses, the three values would likely be close to each other. In contrast, in low‐input systems, YGF (farmer‐ based) will be considerably lower than YGE (experimental) and YGM (model‐based).

Figure 5.5. A conceptual framework depicting the relative rankings of average farmer yields and three measures of yield potential. Different measures of the yield gap (YG) are indicated at the right side of the figure and are as follows: YGM, model‐based yield gap (yield potential is simulated with a model); YGE, experiment‐based yield gap (yield potential is estimated with a

67 69

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact field experiment); and YGF, farmer‐based yield gap (yield potential is estimated with maximum of farmers’ yields) (Source: Lobell et al., 2009).

5.4.2. What contributes to yield gaps? The following five factors that may contribute to the yield gap:

Water quality and availability. The quality and availability of water during (part of) the growing season and limiting current production. Yield losses can be overcome by the supply of good quality irrigation water.

Nutrient availability and efficient management. The availability of nutrients during (part of) the growing season and limiting current production. Yield losses can be overcome by the supply of nutrients in the form of organic and inorganic fertilizers and through efficient nutrient management.

Inadequate crop protection. Reductions in crop yields due to inadequate control of weeds, pests and diseases. Yield losses can be avoided by application of crop protection methods including the use of biocides, phytosanitary methods and crop rotations.

Inadequate application of mechanization and/or labor. Unavailability of and inaccessibility to mechanization and/or labor may cause yield losses. This holds especially for non‐timely or ineffective execution of time‐sensitive cropping operations, such as sowing or planting. Limited availability of ‐ or access to ‐ mechanization and/or labor may in these cases result in delayed sowing/planting, forcing the crop to grow under less favorable conditions.

Inability to assess soil quality (salinity), or inaccessibility to facilities for soil testing at the time of sowing leads to wrong selection of crops and poor soil management. This limitation can be avoided by timely soil testing and selection of suitable soil management practices including conservation agriculture technologies for moisture retention.

Ineffective knowledge systems. Refers to insufficient knowledge (poor link between research‐ extension‐farmer) resulting in untimely or inadequate crop management. Examples are many, e.g. selecting varieties suitable to local conditions, insufficient knowledge on crop nutrient requirements and their application, inadequate insight in soil erosion prevention options and soil conservation technologies, or crop protection management. All may possibly contribute to yield reduction.

Broadly speaking, the concept of crop yield is situated between three scientific disciplines: crop sciences including agronomy, soil and water, and socio‐economics. Crop science and agronomy (biophysical science) tend to focus on proximate factors—such as genotype, energy (e.g. radiation, photoperiod, temperature), soil and water focus on soil fertility and conservation, water in irrigation and drainage, while socio‐economics tend to focus on underlying determinants—such as markets, policy and institutions. The Figure 5.6 below illustrate these three contrasting perspectives.

68 70

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Crop Science Agronomy

(physiology)

Crop Yield

Social Science

Figure 5.6. Determinants of crop yields (Source: Schreinemachers, 2006).

Crop science (physiology) perspective focuses on the level of the individual crop and increase in crop yield is very much an objective itself. The yield of a crop is a function of total biomass and harvest index, which can be increased by crop improvement or use of higher yielding cultivars (Figure 5.7).

Figure 5.7. Yield components from crop physiology perspective (Source: Schreinemachers, 2006).

69 71

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Figure 5.8 shows an agronomy perspective with the focus on the field ratheer than at plant level. The yield of a crop can be increased by improving crop management or improving the interaction between the two.

Figure 5.8. Crop yield from agronomy perspective (Source: Schreinemachers, 2006).

The Figure 5.9 below conceptualizes the socioeconomic perspective on the farm household. It shows that crop yield is one particular outcome of farm decision‐making, rather than an objective in itself. In their decision‐making, farm households are guided by their objectives and their perceptions of the environment, anthropogenic factors, consumer preference for specific traits, the availability and price of inputs, the sale of output, the security of their land tenure, the amount and distribution of rainfall, and the fertility of their soils.

High income Secure income Knowledge Leisure/Hobby Preference Social status

Figure 5.9. Socioeconomic view of crop yield (Adapted from: Schreinemachers, 2006).

70 72

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

The three disciplinary perspectives on crop yield complement rather than substitute each other. Each perspective focuses on a different scale, from the plant, to the plot, and to the farm level.

5.4.3. Estimating crop yield potential Yield potential is a concept, rather than a quantity, which makes estimation both challenging and complicated. By definition, yield potential is an idealized state in which a crop grows without any biophysical limitations other than uncontrollable factors, such as solar radiation, air temperature, and rainfall. Therefore, achieving yield potential requires perfection in the management of all other yield determining production factors such as plant population, the supply and balance of 17 essential nutrients, soil and water conservation, and protection against losses from insects, weeds, and diseases from sowing to maturity. Such perfection is impossible under field conditions, even in relatively small test plots let alone in large production fields. Lobell et al. (2009) considered three main techniques for assessing yield potential and yield gaps over relevant spatial scales, each with its own strengths and weaknesses.

Model simulations. Crop models have been used to estimate crop yield potential at scales ranging from a specific field to a region or country. Most crop models simulate phenological development in relation to photothermal time, net assimilation, resource allocation to different organs, transpiration, and soil water dynamics on a daily or hourly time step. Less sophisticated models simplify simulation of net assimilation by using a standard value for radiation‐use efficiency that accounts for both photosynthesis and respiration; more sophisticated models simulate both photosynthesis and respiration directly. Although most models can simulate yield potential under both irrigated and rainfed conditions, only a few are robust in simulating the impact of other stresses, such as a deficient supply of nitrogen and other nutrients and yield losses from insects, disease, and weed pressure. Despite these differences in sophistication, there are a number of robust crop models that give reasonable estimates of yield potential as estimated by the highest measured yields in research studies and farmers’ fields. To simulate yield potential for a given field requires a minimum set of input data that vary by model but typically include daily maximum and minimum air temperature at canopy height, solar radiation, rainfall, relative humidity, sowing date and depth of seed placement or the date of emergence, the genotype‐specific photothermal phenological development coefficients for the cultivar or hybrid to be simulated, and plant density. For water‐limited yield potential under rainfed conditions, soil texture, initial moisture levels, and effective rooting depth must also be provided as inputs to the model. Information about nutrient supply and pest pressure is not required because it is assumed that these factors do not limit yield.

Field experiments and yield contests. Direct measures of yield potential can be made in field experiments that utilize crop management practices designed to eliminate all yield reducing factors, such as nutrient deficiencies or toxicities, damage from insect pests and diseases, and competition from weeds. Achieving perfect growth conditions throughout the cropping period is quite difficult, and the degree of difficulty rises as test plot size increases from small quadrants of <10m2, which can be intensively managed by hand, to test plots of several hundred m2, which allow use of production scale field equipment but have relatively uniform soil properties, to production‐scale fields of >4 ha that require use of full‐size equipment and typically contain some heterogeneity in soil properties that determine optimal practices for management of inputs, such as nutrients and water. To obtain robust estimates of yield potential for a given

71 73

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact location requires conducting such experiments over many years to ensure that the mean estimate reflects a typical range of climatic variation. In fact, year‐to‐year climate variation is so large at most locations that the best estimates of site yield potential would employ a crop simulation model that has been validated for the site or in the surrounding region based on an adequate number of site years. The combination of simulation and field validations provides a more robust approach for estimating yield potential for a region than using either method alone.

Maximum farmer yields. An alternative but less common approach to estimating yield potential is to observe the maximum yield achieved among a sizable sample of farmers in a region of interest. Typically, estimates must rely on farmer‐reported values rather than direct measurements to achieve large sample sizes, and therefore much care is needed to identify farmers with reliable records for individual fields and to convert all yields to standard moisture content. As an additional step to ensure data quality, one should also obtain independent estimates of yields in a subset of fields, such as by harvesting several small plots within farmers’ fields. The use of maximum farmer yields as a proxy for yield potential is only appropriate in intensively managed cropping systems, where farmers apply levels of fertilizer and pest and disease controls that make it possible to approach yield potential (best practices/bench marking). Although it is still unlikely for a farmer to reach yield potential even with high inputs, among many farmers, it is likely that at least some farmers will come quite close (champion/progressive farmers). Of course, the key here is whether the yield constraints in different fields are in fact independent or, more specifically, whether they are independent enough that maximum yields provide a good approximation for yield potential.

5.4.4. Approaches to study yield gaps Several approaches can be used to study causes of yield gaps, each with their own advantages and shortcomings (Lobell et al., 2009).

On‐farm experiments. The most conceptually straightforward but expensive way to research on‐farm constraints to yields is to conduct controlled experiments that compare alternative management treatments in a series of farmers’ fields. A seminal study using this approach was conducted as part of the International Rice Agroeconomic Network (IRAEN) in six Asian countries, where farmers were enlisted to run experiments side by side with their usual practices. The management aspects that varied in the experiments were chosen on a site‐by‐site basis by researchers, who selected a few factors they felt most likely to improve yields— typically higher fertilizer rates or more intensive insect and weed control measures. Economic surveys were simultaneously conducted to understand the underlying socioeconomic reasons that dictated farmers’ management choices. The results demonstrated three important lessons. First, yields with more intensive management exhibited tremendous variation across study locations, as well as across fields within individual sites. Put differently, the correlation between farmer yields and the yield gain under high inputs was very low. Thus, much of the apparent gap between yields on experiment stations and in farmers yields was attributed to differences in factors governing field‐specific yield potential or to biophysical factors, such as soil quality in those fields. Such field‐specific factors are those related to management practices not included in the studies and other factors affecting yield losses as listed in Table 5.2 below.

72 74

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 5.2. Common factors that contribute to yield losses in farmers’ fields.

Biophysical factors Socioeconomic factors Nutrient deficiencies and imbalances (nitrogen, Limited time devoted to farming phosphorus, potassium, zinc and other essential nutrients) activities Water stress Risk aversion Flooding Inability to secure credit Suboptimal planting (timing and density) Profit maximization Soil problems (salinity, alkalinity, acidity, iron, aluminum or Lack of knowledge on best boron toxicities, compaction and others) practices Weed pressure Insect damage Diseases (head, stem, foliar and root) Lodging (from wind, , hail or snow) Inferior quality of planting material (seed or vegetative)

Second, high inputs improved yields over average farmers’ practices in all situations, by an average of 25 percent in wet‐season on‐farm trials and 30 percent in dry‐season trials. Factorial combinations revealed that much of the gap was attributed to improved fertilizer and insect pest management. Third, the costs and benefits of greater fertilizer rates or insect control were such that yield gains were rarely justified on economic grounds. Although nothing can replace the ability of controlled experiments to uncover causes and effects, researchers have resorted to other indirect but less costly approaches to understand the causes of yield gaps.

Empirical studies of yield heterogeneity. The remarkable heterogeneity of agricultural systems is often overlooked in discussions of crop yields. One manifestation of this heterogeneity is that maximum farmer yields sometimes provide a reasonable estimate of yield potential. This heterogeneity also provides an attractive setting in which to study causes of yield variation as observed in the OSS Batinah survey of 2010. The most straightforward analysis can proceed when, in addition to yield measurements, one has detailed information on the specific soil and management factors likely to affect yields. For example, Calvino and Sadras (2002) studied the statistical relationships between wheat yield, climate, and management data from 103 commercial farms in the Pampas region of Argentina and concluded that management to reduce late‐season water deficits would be the most effective strategy to reducing the yield gap. In the absence of management and soil measurements, it is still possible to learn something about causes by analyzing the pattern of yields in space and time and by comparing these patterns to those expected for different factors. Factors such as soil properties tend to vary gradually across a landscape, whereas management variations follow strict field boundaries. The relative amount of variability seen over short distances therefore provides a useful indicator of the importance of one set of factors (management) relative to another (soil), even if it cannot pinpoint specific factors causing the variation. Similarly, analysis of yields through time can indicate the relative importance of location‐dependent factors, such as farmer skill or soil quality.

73 75

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Models. The same crop growth simulation models used to measure yield potential can also be used to evaluate the yield gains possible with specific management changes. In this approach, controlled simulation experiments are conducted wherein all factors are fixed except for one or two factors on which the analysis focuses. Often the most limiting step in this analysis is knowledge of the existing management practices, which can be assessed with farmer surveys. For example, Aggarwal and Kalra (1994) used the WTGROWS crop model to simulate yield potentials for the optimal sowing date and concluded that Indian wheat yields are reduced by late sowing which in fact is supported by a remote sensing study in the eastern Gangetic plains that estimated 60% of wheat area is sown after the optimum window. Late sowing in these systems, a product of both late harvest of summer rice and the time needed to prepare the fields for sowing under conventional tillage, therefore appears to be a substantial cause of yield gaps, and it is a factor that can be overcome with adoption of existing technologies.

Econometrics. A related but separate body of literature concerns the responsiveness of crop yields (elasticity of yields) to price increases. The relationship between yield elasticities and causes of the yield gap is clear: If yields are highly responsive to prices, then much of the gap must be attributable to input levels and management practices that are readily adjusted, such as fertilizer rates or weed and insect control. Alternatively, low yield elasticities imply that average yields are not constrained by factors amenable to such rapid changes.

5.4.5. What can be done to reduce the yield gap? The following general considerations relative to the management are recommended for producing and sustaining high yields.  A fundamental planning process that estimates what the actual attainable yield levels might be within each field, recognizing existing controllable limiting factors and their interactions for the cropping system. Producing high yields often requires on‐farm experimentation in which a yield goal is set that is slightly out of reach. Then all input levels from seeding rate to variety selection to fertilizer rates are set assuming that we can attain that yield. As we learn, practices are applied to whole fields and farms.  A focus on timeliness of all operations and a record keeping system that allows quantification of what works and what doesn't work.  Use of technologies such as genetically enhanced varieties and site‐specific management to control risk.  Long‐term dedication to soil improvement, including physical, chemical, biological properties and conservation agriculture aspects. Individuals who produce top yields seldom do it overnight.  That's because properties such as soil tilth, water holding capacity, and subsoil characteristics can be improved, but only over a period of several years.  A constant watch for yield limiting factors and dedication to removal of those that can be controlled. Insufficient soil fertility is an example of a controllable limiting factor that can be economically removed, given sufficient time.  Soil fertility programs designed to narrow the yield gap have a goal of removing the potential yield limiting factors by supply of immobile nutrients such as phosphorus (P) and potassium (K).  In marginal (saline) lands, the impact of soil salinity can be eliminated by root zone salinity management using proper leaching fraction and drainage.

74 76

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

5.4.6. OSS perspective The impact of bridging the current yield gap in non‐saline areas is likely makes a very substantial contribution to the . For example, it is estimated that raising crop yields to the average of the top 25 percent found in the OSS surveys would generate at the present value of economy about OMR 450 million and achieving the mean of the top 10 percent of observed yields would generate about OMR 1,000 million (see Vol. 1, Main Report of Oman Salinity Strategy).

The immediate objective should be not for aiming at 'potential yield’ but to achieving the top 10 percent of the observed yields (for example, 7 tonnes/feddan in case of date palm). The extreme variation in yields can be attributed to:  Differences in varieties/cultivars within the crop and  Management practices adopted by different farmers in their respective farms.

Unfortunately the data from OSS surveys do not provide any such information. Nevertheless, as mentioned before, the heterogeneity found in the yield of majority of the crops at given salinity/ soil conditions itself provides a good opportunity to study the causes of yield variation and draw reasonable inferences on what exactly is causing these. The approach to this undertaking would be to conduct an in depth assessment of:  prevailing soil and water conditions in each of the different categories of farms exhibiting these yield variations (e.g. high, medium and low); and  from each category, comparison of a selection of farms (approx. 5‐10 percent) with similar soil and water characteristics for (i) crop related variables such as varietal characteristics, including phenology, planting time, density, seed source or age of plantation (in case of perennial crops), harvest and post‐harvest operations, (ii) farm management variable such as agronomy including soil and water management, nutrient application, plant protection measures), and (iii) socioeconomic data that dictate farmer’s management choices such as status of the farmer, family size, farm size, ownership, alternative sources of income, literacy level and marketing intelligence.

The above undertaking will facilitate the identification of the ‘best performing farms’ and to assess them comprehensively in terms of crops characteristics, management practices and socioeconomic variables to identify ‘factors’ responsible for the high yields. It should also help in the identification of some poor performing farms and as a second step, a selection of these would be targeted for application of the identified ‘best practices’ in terms of crop and management criteria, together with capacity building (where necessary) to improve farmers knowledge and skills. This process of optimization is expected to raise the bar of the poor performing farms to a considerable level (though not reach the top 10 percent observed yields) in a relatively short‐period (3‐5 years). Parallel to the above activities, model/demonstration farms need to be set up in farmer’s fields based on the identified best practices for major crops to serve as the controls and at the same time disseminate the best practices across the Omani farming community.

While the above actions are expected to bridge the gap between maximum and average farmer’s yields, as a long‐term strategy, there is also a simultaneous need to conduct controlled experiments that compare alternative managements treatments which include a few factors that are most likely to improve yields – such as higher fertilizer rates more intensive insect and weed control measures together with optimized use of water and soil resources. These on‐farm

75 77

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact experiments will give an idea of the levels to which yields of major crops can be increased and the gap with potential yield can be bridged in the longer‐term. Given this it is suggested that a project be established that involves partnerships between the Ministry of Agriculture, SQU and farmer groups, with the following objectives:  Trial the combination of factors leading to optimum yields of the major crops of Oman.  Conduct economic analyses of farming systems with different water use efficiency.  Alternative crops that yield better in environments similar to Oman.  Determine factors likely to be limiting livestock production in Oman.  Build competence of farmers to achieve “best practice” yields of the most important crops. It is suggested that following parallel streams of adaptive research and development be conducted: Crop research. Using the research resources of the Ministry of Agriculture and the universities, there should be increased research into the actual requirements of the different crops for water, nutrients and better management. The focus of this work should be on testing the benefits of improved germplasm, better water application techniques and irrigation scheduling, complemented by the use of fertilizers and other management tools. One area that might have early success is the determination of the benefits of micronutrient application on crop yield. Soil surveys conducted as part of OSS project have shown that Oman has some non‐saline soils of high pH; plants growing in these soils may respond to the application of low applications of manganese (Mn) and iron (Fe). The need for this could be confirmed by tissue testing the leaves of plants in relevant environments.

Alternative crops. Given that the livestock populations in Oman have grown substantially in recent years and the two main fodder crops alfalfa and Rhodes grass grown in the Sultanate require large quantities of water (up to 15,700 m3 ha‐1 yr‐1), often drawn from non‐renewable groundwater sources, it is imperative that urgent measures are taken to reduce water demand for the forage production. One way to achieve this is to look at other salt‐tolerant forage crops that need less water to grow. Studies from Oman and the UAE have already shown that native grasses such as buffel grass have significantly lower water requirements (ca. 1,500 mm yr‐1) with very similar yield potential (up to 90 t ha‐1 of green matter), salinity tolerance and nutritional quality as Rhodes grass. Similarly, studies conducted in collaboration with ICBA identified crops like barley, pearl millet, sorghum and fodder beet to have excellent potential as alternative forages in production systems affected by salinity. ICBA studies have also shown that both cowpea and guar could be excellent alternatives forage legumes for the water‐thirsty alfalfa. Both these crops are moderately salt‐tolerant and in addition, they are fast‐growing high quality forages and have other economic uses, especially as vegetables. For highly saline areas, the potential of non‐conventional forage grasses such as Distichlis spicata, Sporobolus virginicus, S. arabicus and Paspalum vaginatum has been demonstrated. These species have been evaluated extensively not only for fodder yield, but also for their nutritional qualities. Productivity levels of about 30‐40 tonnes ha‐1 yr‐1 dry matter at 30 dS/m have been obtained in long‐term trials at ICBA. However, as indicated in Section 4.3 of this report, further development of these forages and their large‐scale adoption requires more research and a dedicated ‘forage improvement program’, with a team of breeders, agronomists and extension specialists, will be necessary to accomplish this.

Economic research. One of the important outcomes of the OSS process has been the development of bio‐economic (linear programming) models of different sized farms with 76 78

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact different levels of salinity. These models, and the capacity in SQU, could be extremely useful in comparing the economic value of different farming systems, thereby providing farmers with decision tools to move from broad‐scale water inefficient cropping systems, to more intensive water efficient systems.

Livestock research. One of the substantial gaps in our knowledge of agricultural systems in Oman is the lack of available information about the livestock production systems and their limitations. A baseline study needs to be conducted to determine the general levels of productivity of livestock systems and the factors most limiting these. This would be a foundation step, leading to more focused R&D on means of overcoming the limiting factors identified.

Participatory research. International experience suggests that one of the best ways to build best practice is for researchers to collaborate directly with farmers. This kind of participatory research should therefore be explicitly promoted and encouraged. In this work, research and extension workers from the Ministry of Agriculture would act in partnership with farmers to demonstrate best practice on farmers’ fields. These demonstrations would be used as part of a technology transfer process to the broader farming community in that area; the technology transfer could involve farmer field days, seminars, media events (print and radio), plant yield competitions, etc. Small experiments could also be conducted by researchers directly on farmers’ fields to determine the benefits of different agronomic manipulations (e.g. different methods of water application, application of macronutrient and micronutrient fertilizers, application of gypsum for sodic soils, etc.). Where possible, this work would be conducted in partnership with larger farmer groups, and the partnerships would be used to support and promote the development of these groups.

5.5. Living with salinity and the role of bio‐saline agriculture Plants differ widely in their ability to tolerate salts in the soil. Furthermore, the extent of yield loss when irrigated with water of a given salinity in any crop depends on a number of factors including: soil type and drainage, method of irrigation and climate, frequency and timing of irrigation, stage of growth and varietal differences. The generally recognized soil salinity classes and their affect of on crop yields are give in the following table (adapted from Abrol et al., 1988).

Table 5.3. Soil salinity classes and the affect on crop yields.

Soil salinity class Conductivity of Effect on crop yields the saturation extract (dS/m) Non saline 0‐2 No significant effect on yield Slightly saline 2‐4 Yields of sensitive crops may be affected Moderately saline 4‐8 Yields of many crops are affected Strongly saline 8‐16 Only tolerant crops yield satisfactorily Very strongly saline >16 Only a few very tolerant crops yield satisfactorily

77 79

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Non‐saline soils (0‐2 dS/m). The yields of almost all crops (including the sensitive) are not significantly affected as long as the soil salinity is kept within 2 dS/m range. Since irrigation even with non‐saline water could contribute substantial amount of salt to a field over the season (for example, a water with EC of 1 dS/m quality suitable for irrigation of most crops contains nearly 1 ton of salt in 1200 m3 of water applied) good soil and water management are important to maintain the soil quality. Soil salinity above 2 dS/m reduces yields, ranging from slight loss to complete failure, depending on the crop and the severity of the salinity problem.

Slightly saline soils (2‐4 dS/m). Crop yield loses may often be minimized by adopting soil and water management and agronomic practices (mitigation) that are appropriate for the local soil, crop and environmental conditions. In particular, the following mitigation techniques help to minimize any negative effects on crop yields.  Proper leveling of soil to prevent accumulation of salts in elevated areas  Deep ploughing to break any hard pan  Mulching and application of organic matter to improve physical properties of soil  Deep irrigation before sowing to migrate the salts from the soil surface  Higher seed rate to compensate for poor germination and priming for uniform stand establishment  Sowing on shoulders of ridges for better growth and yields  Salt scraping and piling away from cultivated areas.

If the crops are salt‐sensitive (e.g. fruits and vegetables), the solutions are:  Increasing leaching to satisfy a leaching requirement greater than 0.25 to 0.30 (negative points: excessive amount of water is required).  Selecting irrigation system with uniform application, high efficiency of irrigation (drip irrigation and mini‐sprinklers).  Scheduling of irrigation through more frequent irrigation with micro‐irrigation systems to enable maintenance of lower levels of salinity in the plant root zone.  Drainage which allows for the leaching of excess salts (in combination with irrigation scheduling).  Soil conditioners ‐ though not recommended because of high price and low efficiency in certain periods/conditions.

If there are limitation to execute the above solutions, consideration must be given changing to a more tolerant variety of the same crop, or to other relatively tolerant crop(s) (adaptation) that will require less leaching to control salts within crop tolerance levels.

Moderately saline soils (4‐8 dS/m). Besides the above mitigatory actions, the most obvious and important management decision is crop selection based upon salt tolerance. For crop selection, the Table 5.4 below serves as a general guide of salt tolerance ratings for the major crops (of Oman), realizing that management practices, crop variety, irrigation water quality, soil type and local climate also affect tolerance.

78 80

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Table 5.4. The salt‐tolerance ratings for the major field and forage crops currently cultivated in Oman.

Sensitive Moderately Moderately Tolerant Highly tolerant (0‐2 dS/m) sensitive tolerant (6‐8 dS/m) (8‐12 dS/m) (2‐4 dS/m) (4‐6 dS/m) Lemon Tomato Wheat Barley None Orange Cucumber Rhodes grass Date palm Mango Pepper Alfalfa Banana Egg plant Sorghum Papaya Cauliflower Coconut Okra Cabbage Onion Water melon Carrot Corn Potato Squash Garlic

Despite the site‐specific and individual nature of sustainable agriculture, several general principles can be applied to help growers select appropriate management practices including selection of appropriate varieties of the existing crops that are well suited to the site and to conditions on the farm including salinity and diversification of crops and cropping systems (alternative crops) and cultural practices to enhance the biological and economic stability of the farm at these salinties. In Oman, almost three decades of research on field crops more than 80 varieties have been found to be promising in 20 crop species from the concerted screening, evaluation and selection. Strategic use of these available genetic resources, together with appropriate soil and water management practices are likely to sustain productivity in these farms. When selecting varieties or crops, the water requirements should also be taken into consideration because of the obvious reason that crops with low water requirements would not only contribute to sustain agricultural productivity but also enhance water productivity, contributing to saving fresh water resources that are otherwise used for irrigation. Strongly saline soils (8‐16 dS/m). Diversification of production systems with crops having much higher levels of tolerance than the existing ones (i.e. alternative crops) can be an important adaptation strategy to alleviate the negative effects of salinity and sustain farm productivity in strongly saline soils. In this context, salt‐tolerant genotypes of annual forages (barley, pearl millet, sorghum, triticale, fodder beet and forage Brassica), cash crops (safflower and sunflower), and perennial grasses (Buffel grass) and shrub species (Sesbania) are likely to be of excellent value. The combinations of summer and winter annual forages and perennial grass and shrub forages, along with proper management packages (especially appropriate irrigation and drainage management to maintain soil salinity within the limit), have already been demonstrated to improve farm productivity and provide options for crop diversification to the farmers in several countries. Very strongly saline soils (>16 dS/m). When growing the tolerant conventional crops (such as those listed above) is no longer economical, introduction of biosaline agricultural systems provides a means of achieving production from saline land and/or water resources, although they do not change the salinity of the land or water resource affected. Thus, for highly saline areas, the potential of non‐conventional /halophytic forage grasses such as Distichlis spicata,

79 81

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Sporobolus virginicus, S. arabicus and Paspalum vaginatum and shrubs such as Atriplex lentiformis, A. canescens and Acacia ampliceps has been demonstrated. These species have been evaluated extensively not only for fodder yield, but also for their nutritional qualities. With the halophytic grasses, productivity levels of about 30‐40 tonnes ha‐1 yr‐1 dry matter at 30 dS/m have been obtained in long‐term trials at ICBA. However, further development of these forages and their large‐scale adoption requires more research and a dedicated ‘forage improvement program’, with a team of breeders, agronomists and extension specialists, will be necessary to accomplish this.

While biosaline agriculture can help to sustain farm production to a large extent, in extreme cases, salinity may also adversely affect the physical and chemical properties of soil, resulting in surface soil compaction and erosion. High levels of salt can dehydrate soil bacteria and fungi and reduce soil health, which is dependent on good microbial activity for the formation of organic matter and nutrient recycling. The breakdown in soil structure, together with the associated loss of plant cover, results in a greater exposure of the soil to erosion. Such badly affected farms may need to be removed from agricultural production if management options to improve salinity are unsuccessful or not economic.

5.6. Main observations  The economic value of intervening to improve agricultural productivity in Oman will depend primarily on the salinity of the groundwater.  At low groundwater salinities, the optimal solution will be to improve the current agricultural system; at higher groundwater salinities, the optimal solution will be to adopt biosaline approaches (better germplasm and management); at intermediate groundwater salinities, the optimal solution will be to adopt a mixed approach.  Improving the current agricultural systems at low salinity areas can be initiated immediately, whereas farms affected by higher salinities can be made sustainable through biosaline agriculture (long‐term approach).  The value to farmers of intervening to improve productivity will be greatest at low salinity and these benefits will decrease as groundwater salinity increases.  Introduction of salt‐tolerant crops in the cropping systems show that the improvement in gross margin is substantial but too low in high salinity farms and subsidies will be required to encourage farmer adoption.

80 82

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

REFERENCES Abrol IP, Yadav JSP and Massoud FI (1988). Salt‐affected soils and their management. FAO Soils Bulletin 39, FAO, Rome. Aggarwal PK and Kalra N (1994). Analyzing the limitations set by climatic factors, genotype, water and nitrogen availability on productivity of wheat. II. Climatically potential yields and management strategies. Field crops Research 38: 93‐103. Ahmed M, Al‐Rawahy, SA and Hussain N (Eds) (2010). A monograph on management of salt‐ affected soils and water for sustainable agriculture. Sultan Qaboos University, Muscat. Ahmed M, Al‐Rawahy SA, Hussain N, Esechie H, Al‐Lawati A, Rahman HA, Shahid SA, Al‐Habsi S and Al‐Rasbi S (2010). Biosaline Agriculture in Oman: A critical review. In: A monograph on Management of Salt‐Affected Soils and Water for Sustainable Agriculture, pp. 9‐16. Ahmad R and Ismail S (1998). Pakistan’s experience in the agricultural use of halophyte species. In: Halophytes and Biosaline Agriculture (edited by R. Choukr‐Allah, C.V. Malcolm, and A. Hamdy), Marcel Dekker, New York, pp. 349‐359. Al‐Lawati A, Al‐Wahaibi H, Al‐Rawahy SA, Al‐Dhuhli H, Al‐Rashdi M and Al‐Bakri AN (2010). Production and water‐use efficiency of alfalfa under different water quantity and quality levels. In: A monograph on Management of Salt‐Affected Soils and Water for Sustainable Agriculture, pp. 61‐65. Allen RG, Pereira LS, Raes D and Smith M (1998). Crop evapotranspiration ‐ Guidelines for computing water requirements – FAO irrigation and drainage paper 56. FAO, Rome. Al‐Rasbi SBAR (2009). The salinity problem in the Sultanate of Oman: Past, present and future perspectives. Report of on expert consultation 26‐29 Nov. 2007 at Dubai, United Arab Emirates. World Soil Resources Reports, 104. FAO, Rome, 46 pp. Anonymous (2011). Oman’s agriculture on a rapid growth trajectory (available at http://omanobserver.om/node/36175). AOAD (Arab Organization for Agricultural Development) (2009). Arab Agricultural Statistics Year Book, Volume 29. AOAD, Khartoum, 430 pp. Ayers RS and Westcot DW (1985). Water quality for agriculture. FAO Irrigation and Drainage Paper 29, FAO, Rome. Barrett‐Lennard EG (2002). Restoration of saline land through revegetation. Agricultural Water Management, 53: 213–226. Barrett‐Lennard EG, Malcolm CV, Stern WR and Wilkins SM (1986). Forage and Fuel Production from Salt Affected Wasteland. Proceedings of a Research for Development Seminar, 19–27 May 1984 at Cunderdin, Western Australia. Elsevier, Amsterdam, 459 pp. Barrett‐Lennard EG, Malcolm CV and Bathgate A (2003). Saltland Pastures in Australia – a Practical Guide, Second Edition. Sustainable Grazing on Saline Lands (a sub‐program of Land, Water and Wool), 176 pp.

81 83

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Barrett‐Lennard E, Mason W, Hannon F, Powell J and Munday B (2005). Australia’s sustainable grazing on saline lands initiative: creating attitudinal change on a grand scale. In: Proceedings of the International Salinity Forum, 25–28 April, Riverside, California. Calvino P and Sadra V (2002). On‐farm assessment of constraints to wheat yield in south‐eastern Pampas. Field Crops Research 74: 1‐11. Evans L (2006). Salinity tolerance in irrigated crops. (Available at: http://www.dpi.nsw.gov.au/agriculture/resources/soils/salinity/crops/tolerance‐irrigated). EAD/ICBA (Environment Agency – Abu Dhabi/International Center for Biosaline Agriculture) (2010). Water Reuse in Agriculture, Forestry and Amenities (Unpublished). FAO (Food and Agriculture Organization of the United Nations) (1986). Irrigation water management: Irrigation needs. Training manual no. 3, FAO, Rome. FAO (Food and Agriculture Organization of the United Nations) (2002). Agricultural Drainage Water Management in Arid and Semi‐Arid Areas. FAO Irrigation and drainage paper. 61, FAO, Rome. FAO (Food and Agriculture Organization of the United Nations) (2009). Oman. Water Report no 34, FAO's Information System on Water and Agriculture (available at http://www.fao.org/nr/water/aquastat/countries_regions/oman/index.stm). FAO/IIASA (Food and Agriculture Organization of the United Nations/International Institute for Applied Systems Analysis) (2000). Global Agro‐ecological Zones (Global‐AEZ)‐2000. (Available at: http://www.iiasa.ac.at/Research/LUC/GAEZ/index.htm). Hatton TJ and Nulsen RA (1999). Towards achieving functional ecosystem mimicry with respect to water cycling in southern Australian agriculture. Agroforestry Systems 45: 203–214. Hussain N (2005). Strategic Plan for combating water and soil salinity in Sultanate of Oman for 2005‐2015. Ministry of Agriculture and Fisheries. ICARDA (International Center for Research in the Dry Areas)/Arabian Peninsula Regional Program (APRP) (2010). Technology transfer to enhance rural livelihoods and natural Resource management in the Arabian Peninsula. Progress report 2009‐2010, 26 pp. IFAD (International Fund for Agricultural development) (2010). Integrated crop‐livestock farming systems. LIVESTOCK Thematic Papers, IFAD, Rome, Italy. Lobell DB, Cassman KG and Field CB (2009). Crop yield gaps: Their importance, magnitudes and causes. Annual Review of Environment Resources 34: 179‐204. Maas EV and Hoffman GJ (1977). Crop salt tolerance – current assessment. Irrigation Science 10: 313‐320. Maas EV and Grattan SR (1999). Crop yields as affected by salinity. In: Skaggs, R.W., van Schilfgaarde, J (Eds), Agricultural Drainage. American Society of Agronomy, Madison, USA, pp. 55–108. MAF (Ministry of Agriculture and Fisheries)/Agriculture Statistics (1997‐2010). Department of Agriculture Statistics, Ministry of Agriculture and Fisheries, Sultanate of Oman. MAF (Ministry of Agriculture and Fisheries) (1993). South Batinah Integrated Study. Directorate General of Agricultural Research, Ministry of Agriculture and Fisheries, Sultanate of Oman.

82 84

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

MAF (Ministry of Agriculture and Fisheries) (1997). North Batinah Integrated Study. Directorate General of Agricultural Research, Ministry of Agriculture and Fisheries, Sultanate of Oman. MAF (Ministry of Agriculture and Fisheries) (2006). Agricultural Census 2004/2005. Department of Statistics and Information. Sultanate of Oman. Marcar N, Crawford D, Leppert P, Jovanovic T, Floyd R and Farrow R (1995). Trees for Saltland: A Guide to Selecting Native Species for Australia. CSIRO Press, East Melbourne, 72 pp. Masters D, Edwards N, Sillence M, Avery A, Revell D, Friend M, Sanford P, Saul G, Beverly C and Young J (2006). The role of livestock in the management of dryland salinity. Australian Journal of Experimental Agriculture 46: 733–741. MoA (Ministry of Agriculture). Comprehensive Report 2005‐2008. Results of activities of ICBA’s projects in Oman. Directorate General of Agriculture & Livestock Research, Ministry of Agriculture, Sultanate of Oman, 119 pp. MoA (Ministry of Agriculture). Agricultural and Livestock Research – Annual Reports 2007‐09. Directorate General of Agriculture & Livestock Research, Ministry of Agriculture. Sultanate of Oman. MoA (Ministry of Agriculture) (2008). The State of Plant Genetic Resources for Food and Agriculture in Oman. Directorate General of Agriculture & Livestock Research, Ministry of Agriculture, Sultanate of Oman. (available at: http://www.pgrfa.org/gpa/omn). Nadaf SK, Al‐Hinai SA, AL‐Farsi SM, Al‐Lawati AH and Al‐Bakri AN (2010). Differential response of salt‐tolerant pearl millet genotypes to irrigation water salinity. In: A monograph on Management of Salt‐Affected Soils and Water for Sustainable Agriculture, pp. 47‐60. Nadaf SK, Galoub HA, Khabotly A, Al‐Lawati AH and Al‐Bakri AN (2006). Report on plant breeding and Biotechnology capacity survey, Oman. FAO document. Draft version. (available at www.globalrust.org/db/.../Oman%20Report%2002%20(edited).doc) Naifer A, Al‐Rawahy SA and Zekri S (2011). Economic impact of salinity: The case of Al Batinah in Oman. International Journal of Agricultural Research 6: 134‐142. National Land and Water Resources Audit (2001). The National Land and Water Resources Audit. Land and Water Australia, Commonwealth of Australia, Canberra. Onuma H (2010). Investigation on present situation and counter measures taken for soil and water salinization. Ministry of Agriculture, 20 pp. Osman AE, Makawi M and Ahmed R (2008). Potential of the indigenous desert grasses of the Arabian Peninsula for forage production in a water‐scarce region. Grass and Forage Science 63: 495‐503. Peacock JM, Ferguson ME, Alhadrami GA, McCann IR, Al Hajoj A, Saleh A and Karnik R (2003). Conservation through utilization: a case study of the indigenous forage grasses of the Arabian Peninsula. Journal of Arid Environments 54: 15‐28. Qureshi RH and Barrett‐Lennard EG (1998). Saline Agriculture for Irrigated Land in Pakistan: A Handbook. Monograph No. 50, Australian Centre for International Agricultural Research, Canberra, 142 pp.

83 85

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Sidahmed OA, Al Rawahy MS and Al Raisy FS (1998). Protected agriculture in the Sultanate of Oman. International Workshop on Protected Agriculture in the Arabian Peninsula, Doha (Qatar), 15‐18 Feb. 1998. Schreinemachers P (2006). The (ir)relevance of the crop yield gap concept to food security in developing countries, Dissertation, Rheinische Friedrich‐Wilhelms‐Universität, Bonn. (Available at http://hss.ulb.uni‐bonn.de/diss_online). Steppuhn H, van Genuchten M Th and Grieve CM (2005a). Root‐zone salinity: I. Selecting a product‐yield index and response function for crop tolerance. Crop Science 45: 209–220. Steppuhn H, van Genuchten M Th and Grieve CM (2005b). Root‐zone salinity: II. Indices for tolerance in agricultural crops. Crop Science 45: 221–232. Van Genuchten MTh and Gupta SK (1993). A reassessment of the crop tolerance response function. Journal of the Indian Society of Soil Science 41: 730‐737.

84 86

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

GLOSSARY OF TERMS Falaj. Water management system used to provide a reliable supply of water for human settlements and irrigation in hot, arid and semi‐arid climates. Feddan. A unit of land area, equaling 0.42 hectare or 1.038 acre. Field crops. A crop (other than fruits or vegetables) that is grown for agricultural purposes. (e.g. cotton, hay, and grain are field crops). Forage crops. Crops (annual or biennal), which are grown to be utilized by grazing or harvesting as a whole crop. Wilayat. An , equivalent of a "province", or "governorate" (plural: Wilayats). Salinity. A measure of the concentration of the soluble salts contained in the soil or water. There are common ways of measuring salinity ‐ by (EC) meter or by measuring the total dissolved solids (TDS) or total dissolved ions (TDI). Electrical Conductivity of soil (ECe) and water (ECw) is measured in dS/m (deci‐Siemens/meter) or mS cm‐1 (micro‐Siemens/ centi‐meter). TDS is measured in units of mg l‐1 (milligrams/liter) or ppm (parts per million). 1 dS/m equals 1mS cm‐1, or 700 mg l‐1 or 700 ppm, and 12 mmoles/l of NaCl. Sodicity. A term given to the amount of sodium held in a soil. Wadi. A valley or a dry riverbed or an intermittent stream that contains water only during times of heavy rain.

85 87

Total

175505 172211 174727 173317 176127 174779 173601 172759 151444 151494 156080 158924 172129 168074 Oman

Musandam 1943 1820 2115 2167 2218 2185 2261 2199 1983 1983 2030 2030 1997 1622

Muscat 8191 8087 8560 8287 8476 8494 8402 8439 5323 5334 5530 5651 5285 4991

Oman Wusta 33 32 118 118 118 112 124 117 17 18 19 19 5 13

of

Sultanate Dhofar 7175 7044 7797 7816 8715 8466 8202 8354 7650 7531 7604 7589 30304 15992 Governorate

86 2010). the ‐

in

(1997

Sharqiyah 18253 18234 18596 19113 19143 19018 19007 18908 20804 20887 21382 21701 21917 24852 governorates

Statistics

and

year

Dakhiliyah 16940 15882 15893 16222 16247 16164 16153 16108 17399 17429 17434 17541 16437 15803 ultural Status and Salinity Impact SalinityImpact and ulturalStatus by

Agricultural

of

productivity

Dhahirah 23462 23747 24133 24372 24550 24039 23853 23607 19796 19954 20915 21645 12878 17266 and

Summary

Batinah 1.

Al 99508 97365 97515 95810 96660 96301 95599 95027 78475 78359 81166 82749 83298 87535 Production

(feddans)

Area,

Area

Annex Agric- 2: Strategy Salinity Oman Appendix A. i. Year 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

88

total

Oman 1232400 1197323 1286635 1213755 1276851 1219104 1196133 1202497 992937 1010696 1078101 1155835 1124045 1502715

Musandam 7080 6441 9615 10738 10880 9068 9456 9684 6967 8220 8640 8640 12887 6239

Muscat 44738 37940 48242 43564 48237 44635 45175 45252 20779 22728 23994 26056 27558 33009

Wusta 368 375 1407 1407 1411 1316 1362 1334 37 85 96 97 22 46

Dhofar 87768 85797 93957 94751 103073 97256 97977 97545 89639 82540 83189 84187 114214 194389 87

Governorate

Sharqiyah 75147 105153 122575 145445 124040 123327 100141 95542 99486 103914 110776 122039 142047 161575

Dakhiliyah 91542 90071 90896 95203 91549 86585 84296 88416 90660 81677 89840 98280 90602 96695 ultural Status and Salinity Impact SalinityImpact and ulturalStatus

Dhahirah 155293 160036 165561 169934 173645 161786 151881 155111 127115 123086 141238 158373 90584 171235

Batinah

(tonnes) Al 770428 711510 754382 652713 724016 695131 705845 709613 558254 588446 620328 658163 676529 839527

Production

ii.

Annex Agric- 2: Strategy Salinity Oman Year 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

89

Total

Oman 7.02 6.95 7.36 7.00 7.25 6.98 6.89 6.96 6.56 6.67 6.91 7.27 6.71 8.65

Musandam 3.64 3.54 4.55 4.96 4.91 4.15 4.18 4.4 3.51 4.14 4.26 4.26 3.85 3.85

Muscat 5.46 4.69 5.67 5.26 5.69 5.25 5.38 5.36 3.9 4.26 4.34 4.61 5.21 6.61

Wusta 11.15 11.72 11.92 11.92 11.96 11.75 10.98 11.4 2.18 4.7 5.06 5.16 4.4 3.5

Dhofar 12.23 12.18 12.05 12.12 11.83 11.49 11.95 11.68 11.72 10.96 10.94 11.09 3.77 12.16 88

Governorate

Sharqiyah 4.12 5.77 6.59 7.61 6.48 6.48 5.27 5.05 4.78 4.98 5.18 5.62 6.48 7.31

Dakhiliyah 5.4 5.67 5.72 5.87 5.63 5.63 5.22 5.49 5.21 4.69 5.15 5.6 5.51 6.1 ultural Status and Salinity Impact SalinityImpact and ulturalStatus

Dhahirah 6.62 6.74 6.86 6.97 7.07 6.73 6.37 6.57 6.42 6.17 6.75 7.32 7.03 9.88

Batinah

(tonnes/feddan) Al 7.74 7.31 7.74 6.85 7.49 7.22 7.38 7.47 7.11 7.51 7.64 7.95 8.12 9.59

Productivity

Annex Agric- 2: Strategy Salinity Oman iii. Year 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

90

2010 18465 9963 52328 87320 238454 25521 905578 284820 12.91 2.56 17.31 3.26

2009 13963 33337 40571 84258 151729 48008 640917 313812 10.87 1.44 15.8 3.72

2008 14163 16286 40219 88257 141095 24576 662539 327625 9.96 1.51 16.47 3.55

2007 13214 16965 37645 88257 130460 25198 610378 312065 9.87 1.49 16.21 3.45

2006 11198 18195 34647 87884 108090 25209 564345 313052 9.65 1.39 16.49 3.56

2005 12267 18192 33101 87884 119138 26561 539839 307397 9.71 1.46 16.31 3.5

2004 16156 14473 42230 99900 163887 23780 722080 292750 10.14 1.64 17.1 2.93

Year

2003 16170 14890 42532 100009 163060 21922 733120 278031 10.08 1.47 17.24 2.78

89

2002 15976 15003 42914 100886 16937 24792 728822 303552 10.14 1.65 16.98 3.01

Oman

2001 16248 15184 43269 101426 172242 25785 765439 313385 10.6 1.7 17.69 3.09 of

2000 15694 14719 42559 100345 151727 24842 692204 344982 9.67 1.69 16.26 3.44 Sultanate

the ultural Status and Salinity Impact SalinityImpact and ulturalStatus in 1999 17132 15135 42394 100066 166914 24464 747441 347816 9.74 1.62 17.63 3.48

year

1998 16967 14149 41523 99572 166527 18090 731695 281011 9.81 1.28 17.62 2.82 and

type

1997 16792 14043 42330 102370 201400 23300 766000 241700 11.99 1.66 18.11 2.36 level)

crop

by

(Country (t/fdn)

(tonnes)

Forages Forages Forages type Production crops crops crops crops crops crops

Crop

Annex Agric- 2: Strategy Salinity Oman B. type Crop Vegetables Field Perennial Fruit Production Vegetables Field Perennial Fruit Productivity Vegetables Field Perennial Fruit

91

2010 15788 1053 350 1118 104 51 4076 2834 1649 517 726 160 93…

page

2009 12017 176 370 1052 81 231 36 7254 1473 1767 402 22056 3 319 66 on

2008 11135 904 543 380 1031 118 51 7513 2382 2862 1725 577 3 1041 182 Continued

2007 10440 843 469 334 970 107 51 7650 2533 3193 1818 600 3 986 182

2006 9006 703 321 243 815 78 32 7911 2813 3788 1979 653 3 891 157

2005 9691 779 394 298 982 0 87 36 7911 2813 3788 1979 653 3 891 157

2004 10493 1658 585 1133 1607 44 339 297 6571 4260 1822 973 313 0 288 246

Years

2003 10612 1565 633 1184 1480 52 288 356 6625 4560 1810 1002 340 0 305 248

2002 10383 1606 571 1156 1610 40 337 273 6614 4641 1846 1002 347 0 306 247 90

2001 10560 1620 600 1192 1673 45 268 290 6235 5075 1869 1060 360 0 330 255

2000 10411 1442 614 1195 1474 45 227 286 5954 5075 1869 1037 270 0 268 246

1999 12164 1502 565 780 1455 45 362 259 6694 4826 1790 935 270 0 380 240 governorate

ultural Status and Salinity Impact SalinityImpact and ulturalStatus and

1998 12395 1508 716 784 1196 11 175 182 6668 4528 1732 805 111 0 260 45

type

1997 11962 1340 1075 762 1320 12 212 109 6594 4362 1637 815 119 0 287 229 crop

by

Batinah Batinah

Governorate Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam production

(feddans) and

type crops

Area Area

Annex Agric- 2: Strategy Salinity Oman C. i. Crop Vegetables Field

92

2010 26112 5183 2400 7273 10540 0 819 0 41558 8196 11403 15944 4622 13 3961 1622

2009 23580 3051 2949 4693 5232 2 805 261 40447 8179 11352 15771 2935 2 3928 1634

2008 23184 6189 2811 3826 3473 3 571 163 40917 12170 11324 15770 2507 13 3921 1634

2007 22160 5368 2448 3461 3526 3 516 163 40917 12170 11324 15770 2507 13 3921 1634

2006 20842 4260 1968 2894 3655 2 437 160 40600 12178 11352 15771 2408 13 3928 1634

2005 20273 4026 1865 2756 3608 2 417 156 40600 12178 11352 15771 2408 13 3928 1634

2004 25870 5816 2195 2177 4047 70 1863 192 52093 11873 11506 14625 2387 3 5949 1464

2003 26054 5856 36587 2188 4090 69 1874 194 52308 11872 11503 14633 2292 3 5470 1463

2002 26287 5908 2227 2207 4128 69 1891 197 53017 11884 11520 14653 2381 3 5960 1468

91

2001 26500 5950 2235 2214 4200 70 1900 200 53365 11905 11543 14677 2482 3 5978 1473

2000 26300 5950 2211 2214 3820 70 1814 180 53145 11905 11528 14667 2252 3 5978 1455

1999 26300 5900 2010 2214 3820 70 1900 180 52357 11905 11528 14667 2252 3 5483 1383

1998 26110 5843 1969 2004 3598 18 1814 177 52202 11868 11465 14641 2139 3 5838 1426 ultural Status and Salinity Impact SalinityImpact and ulturalStatus

1997 26182 5843 2664 2004 3598 18 1814 177 54770 11917 11564 14672 2138 3 5878 1428

Batinah Batinah

Governorate Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam

crops

Annex Agric- 2: Strategy Salinity Oman Crop Forages Fruit

93

95… 2010 205112 11624 3322 17181 653 0 562 0 11486 5079 4248 1597 2541 0 570 page

on

2009 131821 1356 2988 13648 483 0 1178 255 9694 2198 2916 634 32112 2 388 2008 111398 7658 4891 4377 11423 0 833 515 11693 3113 4204 2567 845 4 1848 Continued

2007 103658 7101 4199 3821 10425 0 742 515 11774 3284 4529 2675 860 4 1770

2006 87666 5931 2871 2706 8085 0 532 299 11358 3520 4949 2744 868 4 1515

2005 94920 6316 3309 3451 10323 0 575 245 11408 3529 6084 2725 876 3 1681

Year

2004 113263 12890 4308 12589 16117 292 2572 1856 11365 5695 3177 1641 911 0 577

2003 115821 9188 4457 12436 16650 307 2323 1878 10233 5660 2823 1460 825 0 536

92 2002 111715 12455 4146 12953 16140 272 2525 1732 11677 6259 3232 1700 888 0 607

2001 118610 13057 4519 14134 17378 305.1 2342 1897 11091 7061 3457 1876 1117 0 730 2000 103737 9356 4096 13782 16654 305 2026 1771 10549 7061 3457 1852 986 0 518 1999 121975 9868 4065 9502 16424 305 3078 1708 11505 6734 3137 1561 521 0 600 ultural Status and Salinity Impact SalinityImpact and ulturalStatus 1998 128392 6985 5283 9916 13382 86 1439 1243 8948 4894 2660 1080 158 0 297

1997 152405 11386 9291 10128 15164 92 1576 1358 11345 6794 2830 1362 209 0 373

Batinah Batinah (tonnes/feddan)

Governorate Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat

crops Production

Annex Agric- 2: Strategy Salinity Oman ii. Crop Vegetables Field

94

2010 449620 117534 42358 115537 162796 0 17732 0 173341 36314 46518 47260 28399 45 14145 6239

2009 386842 51971 47520 78686 63192 20 10318 2388 148172 35059 37178 49079 18427 0 15674 10178

2008 381601 104255 47916 58848 58813 47 9091 1967 153439 43325 41219 56299 13112 46.15 14272 5849.7

2007 359506 89338 41504 50346 59746 47 7922 1967 145390 41516 39608 53934 12158 45 13559 5855

2006 344204 71581 33569 43892 62123 37 6898 2042 145219 42053 40289 54571 11464 45 13783 5627

2005 306322 78862 30655 50121 65744 34 6156 1945 145604 38408 50612 43189 12696 0 12367 4522

2004 432317 106483 35909 43473 69671 1042 30105 3080 152668 30043 45022 37839 10837 0 11998 4334 2003 438949 108227 36587 44327 70215 1054 30648 3113 140842 28806 40429 41918 10287 0.99 11641 4107

2002 436404 107746 365444 44320 69112 1044 30577 3075 135335 35326 42663 64354 11116 0 10926 3832

93 2001 458300 113000 38202 46284 73303 1100 32000 3250 136015 40527 45371 61746 11275 6 13165 5280

2000 399600 113000 35200 46284 986 0 518 419 138827 40517 52450 83527 10581 2 13345 5717

1999 466600 104125 34883 37841 66526 1100 33560 2806 154302 44836 48811 73671 10495 2.01 11004 4695

1998 463120 103109 34168 34091 62704 271 31475 2757 111050 45048 47959 60066 9553 180 4116 2247 ultural Status and Salinity Impact SalinityImpact and ulturalStatus

1997 484685 103375 46538 34159 62704 271 31475 2757 121993 33738 32883 29498 9691 5 11314 2578

Batinah Batinah Governorate Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam Al Dhahirah Dakhiliyah Sharqiyah Dhofar Wusta Muscat Musandam

crops

Annex Agric- 2: Strategy Salinity Oman Crop Forages Fruit

95

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact Appendix 2. Soil salinity (dS/m) in Al Batinah governorates – Number and percentage of farms under each salinity class 0‐30 cm Wilayat <2 2‐3 3‐5 5‐7 7‐‐10 10‐15 15‐20 >20 Total Barka 7 1 4 3 2 6 2 4 29 24.1 3.4 13.8 10.3 6.9 20.7 6.9 13.8 Musanaa 8 2 4 1 4 1 0 0 20 40 10 20 5 20 5 0 0 Suwaiq 11 3 9 0 1 2 1 1 28 39.3 10.7 32.1 0 3.6 7.1 3.6 3.6 Khaburah 6 1 3 3 2 3 0 2 20 30 5 15 15 10 15 0 10 Saham 7 4 5 2 0 2 0 0 20 35 20 25 10 0 10 0 0 Liwa 6 1 2 2 1 3 1 2 18 33.3 5.6 11.1 11.1 5.6 16.7 5.6 11.1 Sohar 10 0 4 2 1 2 0 1 20 50 0 20 10 5 10 0 5 Shinas 7 4 5 2 0 2 0 0 20 35 20 25 10 0 10 0 0 Total 62 16 36 15 11 21 4 10 175 35.4 9.1 20.6 8.6 6.3 12 2.3 5.7 30‐60 cm Wilayat <2 2‐3 3‐5 5‐7 7‐10 10‐15 15‐20 >20 Total Barka 8 2 4 2 4 6 0 3 29 27.6 6.9 13.8 6.9 13.8 20.7 0 10.3 Musanaah 8 2 4 1 4 1 0 0 20 40 10 20 5 20 5 0 0 Suwaiq 14 6 4 0 1 2 1 0 28 50 21.4 14.3 0 3.6 7.1 3.6 0 Khaburah 6 2 0 4 2 4 0 2 20 30.0 10.0 0 20 10 20 0 10 Saham 8 2 3 4 2 1 0 0 20 40 10 15 20 10 5 0 0 Liwa 8 1 2 2 3 1 0 1 18 44.4 5.6 11.1 11.1 16.7 5.6 0 5.6 Sohar 10 3 3 3 1 0 0 0 20 50 15 15 15 5 0 0 0 Shinas 8 2 3 4 2 1 0 0 20 40 10 15 20 10 5 0 0 Total 70 20 23 20 19 16 1 6 175 40 11.4 13.1 11.4 10.9 9.1 0.6 3.4

94 96

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Appendix 3. Analysis of the long‐term data on water salinity from 33 farms in Suwaiq, Saham and Barka wilayats a. Suwaiq dataset (Maps 4034 and 3534) The Suwaiq dataset consists of data for 11 bores that have been sampled on up to 13 occasions between March 2006 and December 2009. All but one bore were sampled on at least 11 occasions; 6 bores were sampled on the maximum number of occasions. The original spreadsheet (not presented here) contained some missing values that were reported as zeros; these were stripped out.

Figure A3.1 shows typical variation in ECw with time for 3 bores from the dataset. It is interesting to see that ECw values were both highest and most variable with time for the bore from Farm 4, which was closest to the coast (Figure A3.1). Bores 1.7 km (Farm 3) and 2.9 km (Farm 8) from the coast had much more stable ECw values (Figure A3.1).

25

20

(dS/m) 15

Farm 3 bore 10 of Farm 4

ECw Farm 8 5

0 Dec‐01 Dec‐02 Dec‐03 Dec‐04 Dec‐05 Dec‐06 Date

Figure A3.1. Changes in ECw with time for three typical bores from the Suwaiq dataset. Farm 4 was 0.9 km from the coast, Farm 3 was 1.7 km from the coast and Farm 8 was 2.9 km from the coast. The bores were located at distances of 0.9–2.9 km from the coastline. The highest average ECw (16.4 dS/m) was from the bore closest to the coast (Figure A3.2). An exponential trendline fitted to the dataset was highly significant (P < 0.001).

95 97

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

20

16

(dS/m) 12 y = 8.554x‐1.41 ECw 8 R² = 0.662

Average 4

0 0 1 2 3 Distance from coast (km)

Figure A3.2. Relationship between average ECw (dS/m) and distance from the coast (km) for the 11 farms of the Suwaiq dataset. ECw values were the average of up to 13 measurements collected between March 2006 and December 2009. The distance from the coast was estimated using the ruler tool in Google Earth knowing the GPS location of each farm (see Table A3.1).

Linear correlations were made of all the ECw data against time for all bores. These correlations were significant for 10 of the 11 bores (P < 0.05). The slopes of these correlations provide a measurement of the rate of salinization of the bores (in dS/m per unit time). Using only slope data where the correlations with time were significant, the rate of salinization of the bores was highest at ~1 km from the coast (~1 dS/m per year), declining to ~ 10 percent of this rate at a distance of 2.8 km from the coast (Figure A3.3). An exponential trendline fitted to the dataset was significant (P = 0.044). 1.2

1

0.8 year)

per

salinisation 0.6

of

0.4 (dS/m Rate 0.2 R² = 0.332 0 0 1 2 3 Distance from coast (km)

Figure A3.3. Relationship between rate of salinization of bores and distance from the coast (Suwaiq dataset). Data on the y‐axis are the slopes of linear correlations of ECw with time for up to 13 observations. Data are only used for 10 bores for which the trends with time were significant (P < 0.05). The distance from the coast was estimated in Google Earth knowing the GPS location of each bore (Table A3.1).

96 98

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact b. Saham dataset The Saham dataset consists of data for 11 bores sampled on up to 13 occasions between March 2006 and December 2009. Eight bores were sampled on the maximum number of occasions. The spreadsheet contained some missing values that were reported as zeros; these were stripped out.

Figure A3.4 shows typical variation in ECw with time for 3 bores from the dataset. Again ECw values were both highest and most variable with time for the bore from Farm 5, which was closest to the coast (Figure A3.4). Bores 2.16 km (SHM Farm) and 2.46 km (Farm 10) from the coast had lower and more stable ECw values (Figure A3.4).

25

20

15 (dS/m)

Farm 5 10

ECw SHM Farm

5 Farm 10

0 Apr‐01 Sep‐02 Jan‐04 May‐05 Oct‐06 Date

Figure A3.4. Changes in ECw with time for three typical bores from the Saham dataset. Farm 5 was 1.13 km from the coast, SHM Farm was 2.16 km from the coast and Farm 10 was 2.46 km from the coast.

The bores were located at distances of 1.1–2.5 km from the coastline. The highest average ECw (17.2 dS/m) was from the bore closest to the coast (Figure A3.5). A power trendline fitted to the dataset was significant at P < 0.05.

Linear correlations were made of all the ECw data against time for all bores. These correlations were significant for 7 of the 11 bores (P < 0.05). The slopes of these correlations provide a measurement of the rate of salinization of the bores (in dS/m per unit time). Using only slope data where the correlations with time were significant, the rate of salinization of the bores was highest at ~1 km from the coast (~2 dS/m per day), declining to ~ 25 percent of this rate at a distance of 1.8 km from the coast (Figure A3.6). Somewhat surprisingly, the rate of salinization then increased again as the distance from the coast increased to 2.5 km. The reason for this anomaly is not presently clear. An exponential trendline fitted to the dataset was significant at P < 0.05.

97 99

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

20

16 (dS/m) 12 ECw 8

‐1.07 4 y = 17.22x Average R² = 0.663 0 0 1 2 3 Distance from coast (km)

Figure A3.5. Relationship between average ECw (dS/m) and distance from the coast (km) for the 11 farms of the Saham dataset. ECw values were the average of up to 13 measurements collected between March 2006 and December 2009. The distance from the coast was estimated using the ruler tool in Google Earth knowing the GPS location of each farm (Table A3.1).

2.5

2

1.5 year)

1 per

salinisation

of 0.5 (dS/m Rate 0 0 1 2 3 Distance from coast (km)

Figure A3.6. Relationship between the rate of salinization of bores and distance from the coast (Saham dataset). Data on the y‐axis are the slopes of linear correlations of ECw with time for up to 13 observations. Data are only used for only 7 bores for which the trends with time were significant (P < 0.05). The distance from the coast was estimated in Google Earth knowing the GPS location of each bore (Table A3.1). c. Barka dataset

The Barka dataset is not completely clear (in the original spreadsheet “Sheet 1” there are 11 bores with the header “Farm 1”). Table A3.1 gives GPS readings for these bores and measurements of bore ECw are for 1989, 2004 and 5 regular samplings from March 2006 to July 2007. This dataset is picked up and extended further on the spreadsheet called “Farm 1 & BHW”. However, the latter datasheet also has additional data – a line of numbers at line 5 that has no GPS location, but apparent bore readings after Oct 2007, and 7 lines of additional bore data without GPS readings from lines 16 ‐22 and no data entries before Oct 2007 to allow for cross‐referencing between sheets. The analysis therefore focuses only on the 11 bores from this set: (a) for which we have cross referencing GPS reading, and (b) cross referencing ECw values

98 100

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact from the earlier period of sampling (1989 – July 07). These data are from lines 4 and 6‐15 from “Farm 1 & BHW”.

The Barka dataset consists of data for 11 bores that have been sampled on up to 13 occasions between March 2006 and December 2009. Only one bore was sampled on all occasions, but 6 bores were sampled at least 12 occasions. Again, the spreadsheet contained some missing values that were reported as zeros; these were stripped out.

The bores were located at distances of 3.7–6.6 km from the coastline. The highest average ECw (34.4 dS/m) was from one of the bores closest to the coast (Figure A3.7). An exponential trendline fitted to the dataset was significant at P < 0.01 (r2 = 0.819).

45 40 ‐6.22 35 y = 13747x R² = 0.818 30 25 (dS/m) 20

ECw 15 10 5 0 0 2 4 6 8 Distance from coast (km)

Figure A3.7. Relationship between average ECw (dS/m) and distance from the coast (km) for the 11 farms of the Barka dataset. ECw values were the average of up to 13 measurements collected between March 2006 and December 2009. The distance from the coast was estimated using the ruler tool in Google Earth knowing the GPS location of each farm.

Linear correlations were made of all the ECw data against time for all bores. These correlations were significant for 7 of the 11 bores (P < 0.05). The slopes of these correlations provide a measurement of the rate of salinization of the bores (in dS/m per unit time). Using only slope data where the correlations with time were significant, the rate of salinization of the bores was highest at ~5 km from the coast (~3 dS/m per day) (Figure A3.8). This dataset was also distinguished by having one negative rate of salinization; the reason for this decline in salinization is not known and further information on this would be useful (Figure A3.8).

99 101

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

4 per 3 2 (dS/m

1

year) 0

salinisation 0 2 4 6 ‐1 of ‐2

Rate ‐3 Distance from the coast (km)

Figure A3.8. Relationship between rate of salinization of bores and distance from the coast (Barka dataset). Data on the y‐axis are the slopes of linear correlations of ECw with time for up to 13 observations. Data are used for only 7 bores for which the trends with time were significant (P < 0.05). The distance from the coast was estimated in Google Earth knowing the GPS location of each bore (Table A3.1).

Table A3.1. Distances to the coast for the 33 farms surveyed from the wilayats, Barka, Suwaiq and Saham.

A. Barka Series Site designation GPS location (degrees) Distance to coast (km) N E FARM 1 23.67465 57.99408 4.11 1 23.66897 57.99302 4.74 2 23.66830 57.99757 4.84 3 23.67340 57.98928 4.19 4 23.65550 57.99987 6.30 5 23.66512 57.99268 5.17 6 23.67583 57.98588 3.87 7 23.67907 58.00192 3.66 8 23.67042 58.00062 4.60 9 23.66497 57.99093 5.17 10 23.65262 57.99897 6.63

100 102

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

B. Suwaiq Series Site designation GPS location (degrees) Distance to coast (km) N E SWQ Farm 23.84980 57.39635 1.44 1 23.84702 57.39537 1.77 2 23.84598 57.39950 1.77 3 23.84577 57.40412 1.68 4 23.85352 57.40335 0.87 5 23.85310 57.39855 1.03 6 23.84858 57.39113 1.69 7 23.85110 57.39337 1.37 8 23.83715 57.39170 2.90 9 23.83973 57.38442 2.80 10 23.84618 57.39803 1.79

C. Saham Series Site designation GPS location (degrees) Distance to coast (km) N E SHM Farm 24.18225 56.86072 2.16 1 24.18168 56.86545 1.76 2 24.17980 56.86630 1.77 3 24.18087 56.86827 1.54 4 24.18287 56.86985 1.28 5 24.18635 56.86985 1.13 6 24.18965 56.86638 1.27 7 24.19047 56.86300 1.53 8 24.18430 56.86073 2.06 9 24.18410 56.86473 1.70 10 24.17738 56.86017 2.46

101 103

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Appendix 4. Yields (kg/ha) of major crops in Oman and other countries of the MENA region (Source: AOAD, 2009). Crop Oman Emirates Kuwait S. Arabia Tunisia Morocco Libya Jordan Syria Lemon 6049 18129 ‐ ‐ 14091 17385 10303 18371 25721 Carrot 9927 9109 51000 27000 7941 28673 3769 46250 26567 Wheat 3084 3659 2300 6092 1170 1319 788 634 1440 Barley 2927 ‐ 2001 6000 470 620 490 401 182 Sorghum/Millet 4238 ‐ 2200 2423 ‐ 863 1185 ‐ 747 Onion 20114 2310 3366 24972 4953 23813 1968 24580 15021 Watermelon 31713 30000 22000 20682 2000 38503 13625 45395 15262 Potato 28332 26259 27647 24972 16260 24467 19333 23938 19919 Dates 8513 4088 11034 6280 3053 1852 5357 7915 2493 Cucumber 24533 36863 65587 56522 20625 55438 20000 71056 13622 Eggplant 20397 1078 4906 15294 1875 20471 2000 26640 20445 Okra 16577 ‐ 13055 13684 10000 26614 ‐ 5670 3193 Tomato 44890 72740 84976 35510 44444 70538 21029 51098 40747 Cauliflower 21688 27778 45891 ‐ 15714 23455 8000 27919 18875

102 104

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact Appendix 5. Leaching requirement for various crops grown with different categories of saline water. Crop Salt tolerance

(50% yield Water salinity, ECw (dS/m) loss at ECx) 2 3 4 5 6 7 8 9 10 Alfalfa 10 0.10 0.15 0.2 0.25 0.3 0.35 0.4 Sorghum 12 0.08 0.12 0.17 0.21 0.25 0.29 0.33 0.37 Pearl millet 11 0.09 0.14 0.18 0.23 0.27 0.32 0.36 0.41 Barley 18 0.05 0.08 0.11 0.14 0.17 0.19 0.22 0.25 0.28 Wheat 13 0.08 0.11 0.15 0.19 0.23 0.27 0.31 0.35 Rhodes grass 15 0.07 0.1 0.13 0.17 0.20 0.23 0.27 0.30 0.33 Tomato 7 0.14 0.21 0.29 0.36 Cabbage 7 0.14 0.21 0.29 0.36 Carrot 9 0.11 0.17 0.22 0.28 0.33 Egg plant 5 0.20 0.30 Beans 3 0.33 Onion 4 0.25 0.37 Sweet melon 10 0.10 0.15 0.20 0.25 0.30 0.350 0.40 Pepper 5 0.20 0.3 Date palm 20 0.05 0.07 0.10 0.12 0.15 0.17 0.20 0.22 0.25 Mango 5 0.20 0.30 0.40 Lime 7 0.14 0.21 0.29 0.36 Banana 7 0.14 0.21 0.29 0.36 Papaya 10 0.1 0.15 0.20 0.25 Guava 9 0.17 0.25 0.33 Grapes 6 0.17 0.25 0.33 Coconut 11 0.09 0.14 0.18 0.23 0.27

103 105

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Appendix 6. Case studies

6.1. The Murray Darling Basin of Australia Oman is not unique in its need to contain its profligate use of water to sustain the resource for the longer‐term; the case of the management (and mismanagement) of Australia’s Murray Darling Basin (MDB) is a useful type example. Overview of the Basin (based on Pink 2008) The Basin (Figure A6.1) covers 1,059,000 km2 or about 14 percent of Australia's land area. This catchment falls into the jurisdiction of six governments, the Australian Federal Government and the Governments of the States of New South Wales (56 percent of the Basin's area), Queensland (24 percent), Victoria (12 percent), South Australia (7 percent) and the Australian Capital Territory (0.2 percent).

Figure A6.1. Location of the Murray Darling Basin in Australia. The basin contains Australia's three longest rivers, the Darling (2,740 km), Murray (2,530 km) and Murrumbidgee (1,690 km). About 84 percent of the land in the MDB is owned by businesses engaged in agriculture, and 67 percent of the basin area is used for growing crops and pasture. The MDB receives an average annual rainfall of 530,618 GL. Of this, 94 percent evaporates or transpires, 2 percent drains into the groundwater, and the other 4 percent becomes run‐off. According to the 2006 Australian Census, about 10 percent of Australia's population (2 million people) live in the MDB. The area accounts for almost 40 percent of Australia's farmers. In 2004‐ 05, more than 80 percent of water consumed in the MDB (about 7,720 GL) was consumed by agricultural industries. Of this, 84 percent was surface water, with the balance being groundwater. The bulk of the water was used in the production of bulk commodities, i.e. cotton (1,574 GL or 20 percent of water used for agricultural production in the MDB), dairy farming (1,287 GL or 17 percent), pasture for livestock (1,284 GL or 17 percent), and rice (1,252 GL or 16 percent).

104 106

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

The total Gross Value of Irrigated Agricultural Production (GVIAP) in the MDB was about $4,600 million. Of this: dairy farming generated $938 million (or 20 percent of the total MDB GVIAP, fruit and nuts generated $898 million (or 20 percent), cotton generated $797 million (or 17 percent) and grapes generated $722 million (or 16 percent). However some irrigated crops in the MDB accounted for relatively high levels of GVIAP using relatively low levels of water consumption. For example, fruit and nuts achieved 20 percent of total GVIAP with 5 percent of agricultural water consumption), and vegetables achieved 12 percent of total GVIAP with 2 percent of agricultural water consumption. Other irrigated crops in the MDB accounted for relatively low levels of GVIAP using relatively high levels of water consumption. For example, rice accounted for 6 percent of total GVIAP with 16 percent of agricultural water consumption, and cereals other than rice accounted for 2 percent of total GVIAP but 10 percent of agricultural water consumption. These statistics suggest that there are high value uses for the water, and deregulation of the water market would establish price signals to move the mix of industries in the MDB further towards high value products.

Unsustainability of the present system There have been three clear indicators that the current method of water allocation in the MDB is unsustainable: Loss of biodiversity. Originally the basin area included forests, plains, grasslands, mountain ranges, and both dry and empheral lakes and wetlands. It supported a significant portion of Australia’s biodiversity including species of flora and fauna found nowhere else. These systems were critically dependent on the natural drying and flooding regime at appropriate times of the year. Patterns of rainfall in the MDBC have been highly variable since the original water allocations were made from the system in the 1960s, and exceptionally low rainfall in the droughts of the first decade of the 21st century have caused extensive degradation of forests and wetlands. In an audit of the condition of wetlands and riparian zones of Australia, Sattler and Creighton (2002) noted: “River regulation, dams, diversions, floodplain drainage and agricultural development have affected many wetlands, particularly in the Murray‐Darling Basin”. Monitoring of tree condition on one wetland, Holland et al. (2008) noted that the survival of stands of river redgum trees was dependent on flooding. They reported “that groundwater management and flooding will improve the health of the floodplain vegetation. However, it is important to note that water table lowering alone is not sufficient to reduce plant water stress... Floodplain trees require a low salinity water source (flooding/fresh groundwater) to reduce plant water stress”. Increases in salinity. Increases in salinity, particularly in the lower reaches of the Murray are critical for a variety of reasons. Importantly, the Murray‐Darling system provides 40‐90 percent of the City of Adelaide’s drinking water. One of the major imperatives of river management has been to stabilize the salinity of the river water at Morgan in South Australia. The salinity of the River Murray for the period 1980 to 2000 was below the WHO recommended drinking standards for water for about 20 percent of the time. This was an improvement over the previous 15 years (1965‐1980) for which this percentage was 30 percent (Chartres et al., 2003). Part of this improvement has been achieved with the use of increased entitlement flows into SA, as well as salt mitigation works, in which saline groundwater intruding into the lower reaches of the river are being intercepted by bore fields, with the effluent being disposed of in evaporation basins. Through the MDBC Salinity Strategy, there has been an agreement to limit the time at which the salinity at Morgan exceeds WHO guidelines to 5 percent (Chartres et al., 2003).

105 107

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

On a more sombre note, the lower reaches of the Murray also contain Ramsar listed wetlands of international significance. These provide habitat for more than 30 percent of the migratory waders summering in Australia: vast numbers of water birds – ducks, swans, pelicans, terns, grebes, and migratory sandpipers and endemic shorebirds (stilts, avocets). In September 2008, the Wentworth Group of Concerned Scientists noted that over the prior 5‐6 years, with no flows of freshwater over the barrages, salinity levels in the Coorong and lower lakes had reached salinities of 180‐200 ppt TDS (total dissolved solids) during summer (Wentworth Group of Concerned Scientists, 2008). Acidification of the lower lakes. During the drought from 2003 to 2008 the continued drawdown of water in excess of the basin’s capacity resulted in the level of water at the basin outlet in South Australia decreasing to about 1 m below sea level, with the intrusion of seawater upstream being prevented by the barrage at Goolwa. However, the lakes and stream channels at the lower end of the system are underlain by sulphidic muds, and the lowering of the watertable inside the barrage was so acute that it caused serious acidification of Lake Alexandrina and Lake Albert in South Australia. This condition became so acute that serious consideration was given to flooding these lakes with seawater. For example, on 14 November 2008, the Murray‐Darling Ministerial Council approved a recommendation to prevent acidification of Lakes Alexandrina and Albert opening the barrages if critical acidification thresholds were reached (Department of Sustainability, Environment, Water, Population and Communities 2011). In the event, the council did not have to make this decision because the system was saved by substantial water. Doing more with less – the need for water reform Water allocations to farmers in the MDB were originally set as an entitlement in the 1960s during a period of high rainfall for the basin. It is now generally agreed that these allocations were unrealistically high and that there needs to be a restructuring of allocations reflecting the biophysical reality of a drying landscape. However, the core political issue for the reform of the allocation and pricing of water in the MDB is substantial. Under the Australian Constitution, the responsibility for all issues associated with land and water management rests not with the Federal Government, but the governments of the Australian States and Territories. The MDB is therefore managed by the Murray Darling Basin Authority (previously Commission) under the authority of the Murray‐Darling Basin Ministerial Council. This council is a partnership of six Governments, the Federal Government of Australia and the Governments of the States of New South Wales, Victoria, Queensland, South Australia and the Australian Capital Territory. In practice, water policy reform in the MDB has had to proceed on the basis of intergovernmental consensus, a situation in which it has been difficult to achieve meaningful water reform. Opinions on how well the current system works, vary according to who one asks. Those responsible for administering the system, notably the Murray Darling Basin Authority (previously Commission) trumpet reform success. On the other hand, groups like the Wentworth Group of Concerned Scientists, have indicated that the use of water from the system is unsustainably high, and that critical reform is required (see Box 1). Caught in the middle, the Australian Federal Government has tried to juggle the politics of water allocation and pricing mechanisms across the range of constituencies involved. In October 2010, the Australian Government released a draft Basin Plan, but its conclusions were contentious and a new process of consultation and negotiation with stakeholders has had to commence. It now seems likely that the revised plan will have “watered down” recommendations regarding the 106 108

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact needs for environmental flows through the system. How all of this plays out is still to be determined. Box 1: Input from Wentworth Group of Concerned Scientists

Guiding principles…

1. All Australians have a right to an adequate supply of safe water for domestic use; 2. We all have a responsibility to use water efficiently; 3. Our rivers, groundwater systems and landscapes must be managed to maintain the health of our ecosystems so they can provide for the variety of current and future human needs; 4. Those who use fresh water to create wealth need investment security and should take responsibility for their part in sustainable water management; and 5. Australians must become water literate and understand the effects that water use has on our environment and other people.

…and in the light of this, reform is necessary to:

 protect river health by recovering environmental water in stressed rivers, and avoid the mistakes of the past in our undamaged rivers;  promote opportunity by fully specifying water entitlements and responsibilities, and then removing impediments to water trading; and  engage communities and ensure a fair transition, so no group is asked to bear an unreasonable burden.

6.2. Australia’s National Dryland Salinity Program (NDSP): an example of a national coordinated response to salinity One R&D response to a developing national salinity problem has been Australia’s National Dryland Salinity Program (NDSP). This program conducted research and development into the causes, impacts and management options for dryland salinity in Australia between 1993 and 2005. An archive of the NDSP’s legacy can be found at www.ndsp.gov.au. Three legacy documents on this website summarize:  The NDSP’s achievements in improving our understanding of the causes, impact and means of adapting to dryland salinity (van Bueren and Price, 2004).  Information for catchment managers (Robbins, 2004). This report focuses on: (a) the extent of the problem and future risk, (b) causes of salinity, (c) impacts and costs, (d) what we can do and how we can measure progress, and (e) integrating these responses with other NRM issues.  Information for landholders and their advisors (Powell, 2004). This report was based around a decision‐making sequence of: (a) assessing salinity risk (and the nature of the salinity problem), (b) short‐listing possible approaches to managing this risk, (c) reviewing tactics and management options, (d) considering possible farm to catchment‐scale outcomes from implementing the options (e) deciding on the best approach or approaches, and (f) confirming preferred tactics and options.

107 109

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Over the course of its 12‐year life, the NDSP influenced the research activity of nearly every water and salinity researcher in the agricultural sector across southern Australia; it also impacted on thousands of Australian farmers through the cooperative implementation of whole catchment and more focused solution case studies, the conducting of workshops and conferences, and through the promotion of its activities in the media. Van Buren and Price (2004) identified 6 key final messages that arose as a result of the NDSP (see Box 2). One of the most important outcomes of the NDSP was the way that it moved tactically to adopt developing ideas in saltland management during its life. When the NDSP was initially established, it had no focus on the development of productive uses for salinised resources: at that time this approach was seen as being “defeatist”. However, NDSP was quick to recognize a constituency of farmers and researchers who could see that in many landscapes the reversal of salinity was highly unlikely and that it would be necessary for farmers to live with salinity (the “adaptation response”) for the foreseeable future. NDSP therefore took an interest in Australia’s saline agricultural scientists by sponsoring a series of PURSL (Productive Use and Rehabilitation of Saline Lands) scientific workshops around Australia. This sponsorship was critical as it maintained the research capacity that was later to be so important in the National Sustainable Grazing on Saline Lands (SGSL) initiative.

6.3. Deregulation of water markets and improvements in water use efficiency: example of the Australian rice industry The deregulation of the water market in Australia has provided substantial incentives for Australian farmers to improve the water use efficiency of their enterprises. One example has been the rice growing industry – an industry traditionally associated with the profligate use of irrigation water (source: www.aboutrice.com/facts/fact01.html). During the 1990’s, the Australian rice industry improved its water efficiency by 60%, and the industry has improved its water use efficiency by 44 percent in the last 10 years, despite the worst drought on record (Figure A6.2). Australian rice growers now use 50% less water to grow one kilo of rice than the world average.

Figure A6.2. Improvements in the water use efficiency of the rice industry in the Murrumbidgee Valley in Australia (source: www.aboutrice.com/facts/fact01.html).

108 110

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact

Box 2. Key messages arising from the NDSP (after van Buren and Price, 2004)

Salinity costs are significant and rising, hence responses must be strategic. The costs of dryland salinity are projected to increase by 60–70 percent over the next 20 years, and the best that we can hope for from most of the current recharge control treatments is a slowing of the rate of future salinization.

Profitable options for reversing the trend are generally lacking.

There is not one salinity problem. Results from Groundwater Flow System modeling confirm that the many forms of salinity expression in Australia require a corresponding diversity in response. NDSP advocated a range of strategic responses based on cost: benefit analyses varying from prevention and recovery, to adaptation. These strategies should take into account the development of new farming systems based on the use of more perennial plants, the implementation of engineering works, and the development of productive uses for saline lands.

Integrated catchment management must be seen as only one approach to deal with dryland salinity. In some regions, groundwater flow systems can operate over substantial scales (greater than 50‐100 km) and cross‐catchment action is therefore required to achieve coordinated surface water and groundwater outcomes. In other regions, salinized land is a higher priority issue than salinized water resources. In these areas, planning and management on a more localised ‘community of common concern’ basis is more appropriate.

Vegetation management remains the key to managing water resources, although the cost‐ benefit of revegetating catchments requires careful analysis.

Lack of capacity (skills, management expertise, poor access to information) is an important, but secondary constraint, to managing salinity. The major problem is the lack of commercially attractive treatment options. In the absence of these, it is unrealistic to expect farmers to change their current annual farming systems in favour of perennials or agroforestry.

Improvements in water use efficiency have also carried through to other crops. In Australia, rice is grown in summer from October until March and in rotation with other winter crops such as wheat, barley and maize. Many of the crops grown in rotation with rice use the existing soil moisture from the harvested rice crops, meaning they do not require further irrigation. This allows for further water savings and more efficient water usage, and provides growers with two crops from the one application of water.

Rice growing is Australia’s most regulated agricultural industry in terms of land and water use, and environmental impacts. Much of this regulation has been industry‐initiated. Rice can only be grown on soils that are deemed suitable by the irrigation corporations and/or the relevant State Government departments based on soil textural classification, electromagnetic induction to determine clay depths and sodicity.

109 111

Oman Salinity Strategy - Annex 2: Agricultural Status and Salinity Impact 6.4. References Chartres C, Dr Mirko Stauffacher, Dr Glen Walker, Dr Tom Hatton (2003). Is the River Murray Water Quality Deteriorating? A Salinity Perspective. www.reec.nsw.edu.au/geo/salt/text/ rivermurray%20csiro.pdf. Accessed 6 October 2011. Department of Sustainability, Environment, Water, Population and Communities (2011). Coorong and Lakes Alexandrina and Albert Ramsar Wetland ‐ Fact sheet; www.environment.gov.au/water/publications/environmental/wetlands/coorong‐ factsheet.html. Accessed 6 October 2011. Holland KL, Jolly ID, McEwan KL, Doody TM, White M, Berens V and Souter N (2008). The ‘Bookpurnong Experiment’: will groundwater management and flooding improve the health of the floodplain vegetation? In: Proceedings of 2nd International Salinity Forum, Adelaide, 31 March – 3 April, 4 pp. Pink B (2008). Water and the Murray‐Darling Basin: a Statistical Profile, 2000‐01 to 2005‐06 Report 4610.0.55.007, Australian Bureau of Statistics, Canberra, Australia, 149 pp. Powell J (2004). Dryland Salinity: On‐Farm Decisions and Catchment Outcomes. A guide for leading producers and advisors. Land & Water Australia, Canberra, Australian Capital Territory, 116 pp. Source: www.ndsp.gov.au.

Robins L (2004). Dryland Salinity and Catchment Management — A Resource Directory and Action Manual for Catchment Managers, National Dryland Salinity Program. Land & Water Australia, Canberra, Australian Capital Territory, 174 pp. Source: www.ndsp.gov.au. Sattler P and Creighton C (2002). Wetlands and riparian zones. In: Australian Terrestrial Biodiversity Assessment 2002, National Land and Water Resources Audit, Canberra Australia. Wentworth Group of Concerned Scientists (2008). Submission to Senate Inquiry into The Urgent Provision of Water to the Coorong and Lower Lakes. www.wentworthgroup.org/ blueprints/bluepri. Accessed 6 October 2011.

110 112