This new volume provides an authoritative source of information on Sudan's agriculture up to the present. It includes detailed background on agricultural production systems in various regions of the country, as well as an overview of Sudanese vegetation, climate, hydrology, geology and other important agricultural impact systems. Twenty authors with first-hand experience and specialized knowledge of the area have written an important reference for all researchers in this field.

The historical background of Sudan agriculture. Some egyptian connexions with Sudan agriculture. The vegetation of the Sudan. The climate of the Sudan. Geology of the Sudan. A note on the origins of the soils of the Sudan from the point of View of the man in the field. Soils of the anglo-egyptian Sudan. Transport in the Sudan. Land tenure in agricultural land in the Sudan. Revenue from land and crops. The problem of land fractionation. Education. Nutrition. Crop production. Crops of the Sudan. Weeds in the Sudan. Locusts in the sudan. Organization of agricultural research and the experimental farms. A review of Experimental work. Irrigation in the Sudan. Animal husbandry. Animal foodstuffs. Fertilizers and manures.

Several environmental changes have occurred in the Sudan in the past; several are ongoing; and others are projected to happen in the future. The Sudan has witnessed increases in temperature, floods, rainfall variability, and concurrent droughts. In a country where agriculture, which is mainly rainfed, is a major contributor to gross domestic product, foreign exchange earnings, and livelihoods, these changes are especially important, requiring measurement and analysis of their impact. This study not only analyzes the economy-wide impacts of climate change, but also consults national policy plans, strategies, and environmental assessments to identify interventions which may mitigate the effects. We feed climate forcing, water demand, and macro-socioeconomic trends into a modelling suite that includes models for global hydrology, river basin management, water stress, and crop growth, all connected to the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT). The outcomes of this part of the modeling suite are annual crop yields and global food prices under various climate change scenarios until 2050. The effects of such changes on production, consumption, macroeconomic indicators, and income distribution are assessed using a single country dynamic Computable General Equilibrium (CGE) model for the Sudan. Additionally, we introduce yield variability into the CGE model based on stochastic projections of crop yields until 2050. The results of the model simulations reveal that, while the projected mean climate changes bring some good news for the Sudan, extreme negative variability costs the Sudan cumulatively between 2018 and 2050 US$ 109.5 billion in total absorption and US$ 105.5 billion in GDP relative to a historical mean climate scenario without climate change.

Urbanisation and long-lasting civil wars and conflict mean that the demographic pattern in Sudan is changing drastically. Nevertheless, 60%-80 % of Sudanese engage in subsistence agriculture. Agriculture remains a crucial sector in the economy as a major source of raw materials, food and foreign exchange. It employs the majority of the labour force, and serves as a potential vehicle for diversifying the economy. However, no rigorous studies have explained productivity in this sector in relation to food security. The situation has worsened because agriculture in particular has been neglected since the advent of oil production in the early 2000s. Moreover, Sudan's agricultural growth has been unbalanced, with the majority of irrigated agriculture concentrated in the Centre and a huge disparity in development indicators between the best- and worst-performing regions.Thus, studies show that the vast majority of Sudanese are reported to be food insecure, especially internally displaced persons and in conflict regions such as Darfur, Kordofan and other regions.