Can the cropping systems of the Nile basin be adapted to climate change?

Climate change poses a fundamental threat to agriculture within the Nile basin due to the magnitude of projected impacts and low adaptive capacity. So far, climate change impacts on agriculture for the basin have mostly been assessed for single-cropping systems, which may bias the results considering that the basin is dominated by different cropping systems, with about one-third of the crop area under double cropping. In this study, we simulate single- and double-cropping systems in the Nile basin and assess the climate change impacts on different cropping systems under two scenarios, i.e. “no adaptation” and “adaptation to a late-maturing cultivar”. We find that the mean crop yields of maize, soybean and wheat decrease with future warming without cultivar adaptation. We attribute this to the shortening of the growing season due to increased temperature. The decrease is stronger in all single-cropping systems (12.6–45.5%) than in double-cropping systems (5.9–26.6%). The relative magnitude of yield reduction varies spatially with the greatest reduction in the northern part of the basin experiencing the strongest warming. In a scenario with cultivar adaptation, mean crop yields show a stronger increase in double-cropping systems (14.4–35.2%) than single-cropping systems (8.3–13.7%). In this scenario, farmers could possibly benefit from increasing cropping intensities while adapting to late-maturing cultivars. This study underscores the importance of accounting for multiple-cropping systems in agricultural assessments under climate change within the Nile basin

Modeling and Prioritizing Interventions Using Pollution Hotspots for Reducing Nutrients, Atrazine and \u3cem\u3eE. coli\u3c/em\u3e Concentrations in a Watershed

Excess nutrients and herbicides remain two major causes of waterbody impairment globally. In an attempt to better understand pollutant sources in the Big Sandy Creek Watershed (BSCW) and the prospects for successful remediation, a program was initiated to assist agricultural producers with the implementation of best management practices (BMPs). The objectives were to (1) simulate BMPs within hotspots to determine reductions in pollutant loads and (2) to determine if water-quality standards are met at the watershed outlet. Regression-based load estimator (LOADEST) was used for determining sediment, nutrient and atrazine loads, while artificial neural networks (ANN) were used for determining E. coli concentrations. With respect to reducing sediment, total nitrogen and total phosphorus loads at hotspots with individual BMPs, implementing grassed waterways resulted in average reductions of 97%, 53% and 65% respectively if implemented all over the hotspots. Although reducing atrazine application rate by 50% in all hotspots was the most effective BMP for reducing atrazine concentrations (21%) at the gauging station 06883940, this reduction was still six times higher than the target concentration. Similarly, with grassed waterways established in all hotspots, the 64% reduction in E. coli concentration was not enough to meet the target at the gauging station. With scaled-down acreage based on the proposed implementation plan, filter strip led to more pollutant reductions at the targeted hotspots. Overall, a combination of filter strip, grassed waterway and atrazine rate reduction will most likely yield measureable improvement both in the hotspots (\u3e20% reduction in sediment, total nitrogen and total phosphorus pollution) and at the gauging station. Despite the model’s uncertainties, the results showed a possibility of using Soil and Water Assessment Tool (SWAT) to assess the effectiveness of various BMPs in agricultural watersheds

Historical climate impact attribution of changes in river flow and sediment loads at selected gauging stations in the Nile basin

The Nile basin is the second largest basin in Africa and one of the regions experiencing high climatic diversity with variability of precipitation and deteriorating water resources. As climate change is affecting most of the hydroclimatic variables across the world, this study assesses whether historical changes in river flow and sediment loads at selected gauges in the Nile basin can be attributed to climate change. An impact attribution approach is employed by constraining a process-based model with a set of factual and counterfactual climate forcing data for 69 years (1951–2019), from the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). To quantify the role of climate change, we use the non-parametric Mann-Kendall test to identify trends and calculate the differences in long-term mean annual river flow and sediment load simulations between a model setup using factual and counterfactual climate forcing data. Results for selected river stations in the Lake Victoria basin show reasonable evidence of a long-term historical increase in river flows (two stations) and sediment load (one station), largely attributed to changes in climate. In contrast, within the Blue Nile and Main Nile basins, there is a slight decrease of river flows at four selected stations under factual climate, which can be attributed to climate change, but no significant changes in sediment load (one station). These findings show spatial differences in the impacts of climate change on river flows and sediment load in the study area for the historical period

Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumption

This research article was published by Hydrology and Earth System Sciences, 2022In most (sub)-tropical African cultivated regions, more than one cropping season exists following the (one or two) rainy seasons. An additional cropping season is possible when irrigation is applied during the dry season, which could result in three cropping seasons. However, most studies using agro-hydrological models such as the Soil and Water Assessment Tool (SWAT) to map blue and green evapotranspiration (ET) do not account for these cropping seasons. Blue ET is a portion of crop evapotranspiration after irrigation application, while green ET is the evapotranspiration resulting from rainfall. In this paper, we derived dynamic and static trajectories from seasonal land use maps to represent the land use dynamics following the major growing seasons to improve simulated blue and green water consumption from simulated evapotranspiration in SWAT+. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by a spatial mapping of the ET results. Additionally, the SWAT+ blue and green ET were compared with the results from the four remote sensing data-based methods, namely SN (Senay), EK (van Eekelen), the Budyko method, and soil water balance method (SWB). The results show that ET with seasonal representation is closer to remote sensing estimates, giving higher performance than ET with static land use representation. The root mean squared error decreased from 181 to 69 mm yr−1, the percent bias decreased from 20 % to 13 %, and the Nash–Sutcliffe efficiency increased from −0.46 to 0.4. Furthermore, the blue and green ET results from the dynamic SWAT+ model were compared to the four remote sensing methods. The results show that the SWAT+ blue and green ET are similar to the van Eekelen method and performed better than the other three remote sensing methods. It is concluded that representation of seasonal land use dynamics produces better ET results, which provide better estimations of blue and green agricultural water consumption

Evaluation and application of multi-source satellite rainfall product CHIRPS to assess spatio-temporal rainfall variability on data-sparse Western margins of Ethiopian Highlands

The spatio-temporal characteristic of rainfall in the Beles Basin of Ethiopia is poorly understood, mainly due to lack of data. With recent advances in remote sensing, satellite derived rainfall products have become alternative sources of rainfall data for such poorly gauged areas. The objectives of this study were: (i) to evaluate a multi-source rainfall product (Climate Hazards Group Infrared Precipitation with Stations: CHIRPS) for the Beles Basin using gauge measurements and (ii) to assess the spatial and temporal variability of rainfall across the basin using validated CHIRPS data for the period 1981-2017. Categorical and continuous validation statistics were used to evaluate the performance, and time-space variability of rainfall was analyzed using GIS operations and statistical methods. Results showed a slight overestimation of rainfall occurrence by CHIRPS for the lowland region and underestimation for the highland region. CHIRPS underestimated the proportion of light daily rainfall events and overestimated the proportion of high intensity daily rainfall events. CHIRPS rainfall amount estimates were better in highland regions than in lowland regions, and became more accurate as the duration of the integration time increases from days to months. The annual spatio-temporal analysis result using CHIRPS revealed: a mean annual rainfall of the basin is 1490 mm (1050-2090 mm), a 50 mm increase of mean annual rainfall per 100 m elevation rise, periodical and persistent drought occurrence every 8 to 10 years, a significant increasing trend of rainfall (similar to 5 mm year(-1)), high rainfall variability observed at the lowland and drier parts of the basin and high coefficient of variation of monthly rainfall in March and April (revealing occurrence of bimodal rainfall characteristics). This study shows that the performance of CHIRPS product can vary spatially within a small basin level, and CHIRPS can help for better decision making in poorly gauged areas by giving an option to understand the space-time variability of rainfall characteristics

Seasonal profitability of soil and water conservation techniques in semi-arid agro-ecological zones of Makanya catchment, Tanzania

This research article published by Elsevier B.V., 2021Soil and water conservation techniques are known to be profitable and widely promoted in sub-Saharan Africa. However, how their profitability vary across cropping seasons has not been fully explored. Thus, farmers are often faced with the dilemma of which agricultural technique(s) and/or combination(s) thereof to implement in which cropping seasons, and for which crops to maximize profits. In this paper, we investigated the profitability of two soil and water conservation techniques (terraces and borders) and compared them against the conventional flat cultivation in Makanya catchment Tanzania. Farmers in the area grow maize, beans, lablab and cowpeas over three cropping seasons (locally called masika, vuli and chamazi/kipupwe). Based on field survey of 382 farmers in 2019, it was found that aggregate yields were generally higher on fields with intercrop than those with monocrop with more than 0.5 ton/ha of total grain yields. Borders were generally more profitable (399 USD/ha) than terraces and flat cultivation during all three cropping seasons while flat cultivation was more lucrative during the masika than vuli season. Terraces was only lucrative for rainfed beans with Benefit Cost Ratio of 1.5 (208.7 USD/ha) and 1.2 (90.5 USD/ha) in masika and vuli respectively. Beans grown on borders during chamazi season had the highest profitability with Benefit Cost Ratio of 1.9 (399 USD/ha) compared to terraces and flat cultivation in all three cropping seasons. Whereas it was more profitable to grow maize, beans and lablab on borders, farmers could still realize appreciable profits by growing these crops as purely rainfed on flat cultivation especially during the masika season. It was concluded that in semi-arid zones, soil and water conservation techniques used in combination with other auxiliary practices such as irrigation, intercropping with legumes, mulching and manure application could greatly enhance profitability, but that depends on cropping season and market factors

How Can We Represent Seasonal Land Use Dynamics in SWAT and SWAT+ Models for African Cultivated Catchments?

This research article published by MDPI, 2020In SWAT and SWAT+ models, the variations in hydrological processes are represented by Hydrological Response Units (HRUs). In the default models, agricultural land cover is represented by a single growing cycle. However, agricultural land use, especially in African cultivated catchments, typically consists of several cropping seasons, following dry and wet seasonal patterns, and are hence incorrectly represented in SWAT and SWAT+ default models. In this paper, we propose a procedure to incorporate agricultural seasonal land-use dynamics by (1) mapping land-use trajectories instead of static land-cover maps and (2) linking these trajectories to agricultural management settings. This approach was tested in SWAT and SWAT+ models of Usa catchment in Tanzania that is intensively cultivated by implementing dominant dynamic trajectories. Our results were evaluated with remote-sensing observations for Leaf Area Index (LAI), which showed that a single growing cycle did not well represent vegetation dynamics. A better agreement was obtained after implementing seasonal land-use dynamics for cultivated HRUs. It was concluded that the representation of seasonal land-use dynamics through trajectory implementation can lead to improved temporal patterns of LAI in default models. The SWAT+ model had higher flexibility in representing agricultural practices, using decision tables, and by being able to represent mixed cropping cultivations