Abstract:Despite the recent interest in biochar and digestate as soil amendments for improving soil quality and increasing crop production, there is inadequate knowledge of the effect of the combination of biochar and digestate, particularly under saline irrigation conditions. A pot experiment with Chinese melon was conducted in a greenhouse, biochar (5%) and digestate (500 mL/pot) were used with and without the recommended mineral NPK (Nitrogen, Phosphorus and Potassium) fertilizer dose (120-150-150 Kg ha −1 ). The plants were irrigated with tap water (SL0) and 2 dS/m (SL1) NaCl solution. The growth, photosynthesis rate, water use efficiency (WUE) and yield of Chinese melon were affected positively when biochar was combined with digestate amendment, particularly under saline irrigation water with and without mineral NPK fertilizer. The maximum yield under normal water was obtained by digestate (SL0: 218.87 t ha −1 ) and biochar amendment combined with digestate (SL1: 118.8 t ha −1 ) under saline water. The maximum WUE values were noticed with the biochar and digestate combination under all water treatments (SL0: 32.2 t ha −1 mm −1 and SL1: 19.6 t ha −1 mm −1 ). It was concluded that digestate alone was more effective than the use of biochar, particularly with normal water. The combination of biochar with digestate had a significant effect on the Chinese melon growth, photosynthesis rate, water use efficiency and yield under saline irrigation, and it can be used as an alternative fertilizer for mineral NPK fertilizer.

North Darfur of Sudan is located on the edge of the Sahara Desert and endures frequent droughts due to water shortages and high summer temperatures. Monitoring and understanding drought characteristics are essential for integrated drought risk mitigation and prevetion of land degradation. This study evaluates drought conditions in North Darfur by analyzing the spatiotemporal distribution of drought using three drought indices (Standardized Precipitation Index, Vegetation Condition Index, and Soil Moisture Content Index) and their combined drought index (CDI) from 2004 to 2013. Biophysical and socioeconomic indicators are further used to measure vulnerability to drought risk and its three components (exposure, sensitivity, and adaptive capacity) through a comprehensive risk assessment framework. The results show that most of North Darfur has experienced prolonged droughts during the study period, especially from 2007 to 2011. There is also a significant correlation between the monsoon season CDI and annual crop yield anomaly. The results confirm the validity of the CDI index, which provides a comprehensive description of the drought situation by combing four drought indices quantifying different drought aspects. The vulnerability results show that the majority of this region is highly exposed and sensitive to drought risks. In particular, the northern zone of the region is highly vulnerable, which is categorized by less‐crop diversity, higher land degradation, frequent droughts, and high‐poverty levels. This study provides valuable information for coping with climate change‐induced drought risk in this region and demonstrates that there is still a large room for enhancing the adaptation capacity in this region.

An experiment was conducted at the Wadi Soba farm, Khartoum-Sudan. The aim of this study is to estimate the Exchangeable Sodium Percentage (ESP) function to Sodium Adsorption Ratio. In this study, linear regression model (ESP -SAR model) for predicting soil ESP from SAR was suggested. For this purpose, 30 soil samples were collected from the field of experiment, soil ESP was estimated from soil SAR in order to compare the predicted results with measured SAR using laboratory tests on saline and non-saline soil samples. The results show that on saline soil Original Research Articlesamples, the Standard Error of Mean (SEM) of predicted ESP obtained by ESP -SAR model was (0.9389) and the P-value was (0.0572). On non-saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by ESP -SAR model was (0.2920) and the P-value was (0.2628). The statistical results indicated that the linear regression model (ESP -SAR model), ESP= 0.84 × SAR + 2.17 with R 2 = 0.7347 has a good performance in predicting soil ESP from SAR meanwhile the ESP -SAR model reflected more accuracy on non-saline soil samples and it can be recommended for both saline soil and non-saline soil samples.

The relationships between soil physical and chemical properties play a key role in facilitating the measurement of soil properties, particularly Exchangeable Sodium percentage (ESP) measurement, which is often using laborious and time-consuming laboratory tests. The aim of this study is to investigate the efficiency of the United States Salinity Laboratory (USSL) model and the ESP-SAR model for prediction of exchangeable Sodium percentage (ESP) from Sodium Adsorption Ratio (SAR) on saline and non-saline soil samples. For this purpose, 23 soil samples were collected from the field of experiment, Jabal Awliya, south of Khartoum state, Sudan. Exchangeable Sodium Percentage (ESP) was estimated as a function of soil SAR in order to compare the predicted results with measured ESP using laboratory tests. The results show that on saline soil samples, the Standard Error of Mean (SEM) of predicted ESP obtained by USSL model and ESP-SAR model was (1.084) and (1.463) respectively. On non-saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by USSL model was (0.7034) and (0.6070) for ESP-SAR model. The statistical results indicated that USSL model has a good prediction on saline soil samples compared with ESP-SAR model. On non-saline soil samples, USSL model showed less prediction performance than ESP-SAR model. It can be concluded that the United States Salinity Laboratory model can be recommended on saline soil samples and ESP-SAR model is more reliable on non-saline soil samples.