Modelling soil erosion response to sustainable landscape management scenarios in the Mo River Basin (Togo,West Africa)

The rural landscapes in Central Togo are experiencing severe land degradation, including soil erosion. However, spatially distributed information has scarcely been produced to identify the effects of landscape pattern dynamics on ecosystem services, especially the soil erosion control. In addition, relevant information for sustainable land and soil conservation is still lacking at watershed level. On this basis, using the LAndscape Management and Planning Tool for the Mo River basin (LAMPT_Mo), we (1) modelled soil erosion patterns in relation with land use/cover change (LUCC), land protection regime, and landforms, and (2) examined the efficiency of landscape redesign options on soil erosion amounts at basin scale. We found that Simulated historical net soil loss (NSL) for the Mo basin were approximately 26, 23, 27, and 44 t/ha/yr, for 1972, 1987, 2000, and 2014, respectively. These simulated NSLs were higher than the tolerable soil loss limits for the Tropics. Steep slopes (≥ 15°), poorly covered lands (croplands and savannas), and riversides (distances ≤ 100 m) are critical areas of sediment sources. The local appraisal of soil loss was in line with the simulated outputs even though quantification was not accounted for when dealing with rural illiterate people. Furthermore, results showed that the examined management measures, such as controlling the identified erosion hotspots through land protective measures, could help reduce the NSL up to 70%, to values closer to the tolerable limits for the Tropics. The model implementation in the basin showed insights for identifying erosion hotspots and targeting soil conservation planning and landscape restoration measures

Stochastic ARIMA model for annual rainfall and maximum temperature forecasting over Tordzie watershed in Ghana

The forecast of rainfall and temperature is a difficult task due to their variability in time and space and also the inability to access all the parameters influencing rainfall of a region or locality. Their forecast is of relevance to agriculture and watershed management, which significantly contribute to the economy. Rainfall prediction requires mathematical modelling and simulation because of its extremely irregular and complex nature. Autoregressive integrated moving average (ARIMA) model was used to analyse annual rainfall and maximum temperature over Tordzie watershed and the forecast. Autocorrelation function (ACF) and partial autocorrelation function (PACF) were used to identify the models by aid of visual inspection. Stationarity tests were conducted using the augmented Dickey–Fuller (ADF), Mann–Kendall (MK) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests respectively. The chosen models were evaluated and validated using the Akaike information criterion corrected (AICC) and also Schwartz Bayesian criteria (SBC). The diagnostic analysis of the models comprised of the independence, normality, homoscedascity, P–P and Q–Q plots of the residuals respectively. The best ARIMA model for rainfall for Kpetoe and Tordzinu were (3, 0, 3) and (3, 1, 3) with AICC values of 190.07 and 178.23. That of maximum temperature for Kpetoe and Tordzinu were (3, 1, 3) and (3, 1, 3) and the corresponding AICC values of 23.81 and 36.10. The models efficiency was checked using sum of square error (SSE), mean square error (MSE), mean absolute percent error (MAPE) and root mean square error (RMSE) respectively. The results of the various analysis indicated that the models were adequate and can aid future water planning projections

An Approach for Simulating Soil Loss from an Agro-Ecosystem Using Multi-Agent Simulation: A Case Study for Semi-Arid Ghana

Soil loss is not limited to change from forest or woodland to other land uses/covers. It may occur when there is agricultural land-use/cover modification or conversion. Soil loss may influence loss of carbon from the soil, hence implication on greenhouse gas emission. Changing land use could be considered actually or potentially successful in adapting to climate change, or may be considered maladaptation if it creates environmental degradation. In semi-arid northern Ghana, changing agricultural practices have been identified amongst other climate variability and climate change adaptation measures. Similarly, some of the policies aimed at improving farm household resilience toward climate change impact might necessitate land use change. The heterogeneity of farm household (agents) cannot be ignored when addressing land use/cover change issues, especially when livelihood is dependent on land. This paper therefore presents an approach for simulating soil loss from an agro-ecosystem using multi-agent simulation (MAS). We adapted a universal soil loss equation as a soil loss sub-model in the Vea-LUDAS model (a MAS model). Furthermore, for a 20-year simulation period, we presented the impact of agricultural land-use adaptation strategy (maize cultivation credit i.e., maize credit scenario) on soil loss and compared it with the baseline scenario i.e., business-as-usual. Adoption of maize as influenced by maize cultivation credit significantly influenced agricultural land-use change in the study area. Although there was no significant difference in the soil loss under the tested scenarios, the incorporation of human decision-making in a temporal manner allowed us to view patterns that cannot be seen in single step modeling. The study shows that opening up cropland on soil with a high erosion risk has implications for soil loss. Hence, effective measures should be put in place to prevent the opening up of lands that have high erosion risk

Increased seasonal rainfall in the twenty-first century over Ghana and its potential implications for agriculture productivity

The slightest change in rainfall could have a significant impact on rain-fed agriculture in countries like Ghana. This study evaluated for the first time the performance of the statistical downscaling model (SDSM-DC) at 2m spatial resolution in simulating rainfall in Ghana for the base period 1981–2010. It further analysed the projected changes in seasonal rainfall pattern across different agro-ecological zones for the twenty-first century under RCP 4.5 and 8.5 emission scenarios over Ghana. Ensemble mean of simulated rainfall data (2011–2099) generated by 43 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used as base factors for local future climate scenarios generation. Performance analysis of SDSM-DC shows a Nash–Sutcliffe efficiency, percent bias and RMSE observations standard deviation ratio of 0.88, −19 and 0.34, respectively. Generally, seasonal rainfall amount is expected to increase between 10 and 40% in all the agro-ecological zones in Ghana by the end of the twenty-first century. Off-season rainfall in December–February shows more than 100% increase in the Guinea Savannah zone. Rainfall projected under RCP 4.5 was on average 2% higher than RCP 8.5 in all the seasons throughout the century. Based on these results, it is appropriate to suggest a high incidence of flooding across Ghana in the twenty-first century. This could have dire consequences on agriculture which contribute to a large proportion of Ghana’s GDP. Therefore, for sustainable food production and security in the twenty-first century, Ghana needs climate adaptation policies and programmes that encourage the design and implementation of early warning systems of meteorological hazards and the introduction of new crop varieties that are flood tolerant.</p

Assessing the Effects of Anthropogenic Land Use on Soil Infiltration Rate in a Tropical West African Watershed (Ouriyori, Benin)

Soil infiltration at a watershed scale is important for understanding and predicting the hydrological process in soil-water-plant systems. This study investigated the effects of land use (LU) conversion on the infiltration rate in the Ouriyori watershed. To that end, in situ infiltration was carried out over the watershed under thirty-six pairs of adjacent cropland-fallow plots using the hood infiltrometer. Saturated hydraulic conductivity (Ks), soil properties, and soil classes were further compared. Results showed a high variability of Ks following the LU classes with a coefficient of variation greater than 60%. After data log transformation, the mean values of Ks showed high infiltration and ranged between 2.59 and 2.42 cm d-1, respectively, for fallow land and cropland. Thus, Ks was relatively lower in cropland compared to fallow land. Hence, the low infiltration recorded in croplands indicated the degradative impacts of unceasing tillage operations for crop production without crop residue incorporation into the soil during tillage. There was no significant difference in bulk density and soil texture in both types of land use. Considering soil classes, the highest infiltration rate was found in Ferric Luvisol and the lowest rate in Dystric Gleysol, meaning that the high infiltration observed in Ferric Luvisol was due to the abundance of soil macropores. Change in natural vegetation to croplands induced a low infiltration rate and macropore connectivity. Moreover, fallow lands tend to provide water storage capacity through the improvement of mesopores, while soil compaction through agricultural activities reduces soil porosity and therefore soil infiltration. In addition, the paired Student's t-Test performed on the transformed data was statistically significant, indicating a difference between Ks under cropland and Ks under fallow land. To improve soil and water conservation for crop production as well as for sustainable rural populations' livelihoods in the watershed, occasional fallowing may be observed to dampen infiltration hindering soil surface conditions