ALBERT

Description: Establishing food security in sub-Saharan African countries requires a comprehensive and high resolution understanding of the driving factors of crop production. Poor soil and adverse climate conditions are among the major drivers of poor regional crop production. Drought and rainfall variability challenges are not fully being addressed by rainfed producers in semiarid areas. In this study, we analysed the spatiotemporal rainfall variability (STRV) and its effects on pearl millet yield using two seasons of data collected from 38 rain gauge stations scattered randomly in farm plots within a 1500 ha area of semiarid central Tanzania. The STRV effects on pearl millet yield under flat and tied ridge management were analysed. Our results show that seasonal rainfall can vary significantly for neighboring fields at distances of less than 200 m, which impacts yield. The STRV for daily rainfall was found to be more critical than for total seasonal rainfall amounts. Scattering fields can help farmers avoid total harvest loss by obtaining at least some yield from the areas that received adequate rain. The use of tied ridges is recommended to conserve soil moisture and improve yields more than flat cultivation in semiarid areas.

Description: Water, Vol. 10, Pages 1245: Describing and Visualizing a Water–Energy–Food Nexus System Water doi: 10.3390/w10091245 Authors: Aiko Endo Terukazu Kumazawa Michinori Kimura Makoto Yamada Takaaki Kato Kouji Kozaki The objective of this study is to describe a target water–energy–food (WEF) nexus domain world including causal linkages and trade-off relationships between WEF resources and their stakeholders, and to develop a WEF nexus system map as an interdisciplinary tool used for understanding the subsequent complexity of WEF nexus systems. An ontology engineering method, which is a qualitative method, was applied for the replicability of the WEF nexus domain ontology and the map, because ontology engineering is a method of semantic web development for enhancing the compatibility of qualitative descriptions logically or objectively. The WEF nexus system map has three underlying concepts: (1) systems thinking, (2) holistic thinking, and (3) an integrated approach at an operational level, according to the hypothesis that the chains of changes in linkages between water, energy, and food resources holistically and systemically affect the WEF nexus system, including natural and social systems, both temporally and spatially. This study is significant because it allows us to (1) develop the WEF nexus domain ontology database, including defining the concepts and sub-concepts of trade-offs relating to WEF for the replicability of this study; (2) integrate the qualitative ontology method and quantitative network analysis method to identify key concepts serving as linkage hubs in the WEF nexus domain ontology; and (3) visualize human–nature interactions such as linkages between water, energy, and food resources and their stakeholders in social and natural systems. This paper also discusses future challenges in the application of the map for a science–policy–society interface.

Description: Water, Vol. 10, Pages 843: The Impact of Multiple Typhoons on Severe Floods in the Mid-Latitude Region (Hokkaido) Water doi: 10.3390/w10070843 Authors: Nobuaki Kimura Hirohide Kiri Iwao Kitagawa Mid-latitude regions in the North Pacific are generally vulnerable to climatological disasters and are possibly more sensitive to future climate changes. Severe flood disasters struck Hokkaido in August 2016 because of the multiple, continuous typhoons that struck the island. We evaluated the effect of these typhoons on floods and changes in future floods using a distributed hydrological model in a watershed located in eastern Hokkaido. We conducted two numerical examinations: a simulation with a major typhoon only (which caused flood disasters) without other preceding typhoons, and a simulation with a simple assumed future climate (in which we employed higher precipitation). The result of the former simulation demonstrated that the impact of the preceding typhoons on the highest flood peak was significant during the early stage of the major typhoon but weaker after the middle stage of the major typhoon. The result of the latter simulation indicated that flood peaks potentially increased with an increase in precipitation. Based on the water level distributions in the surface layer, the impact of multiple typhoons and future weather conditions on potential flood peaks depends on the degree of soil saturation over our target watershed.

Description: Paired impermeable or porous obstructions are used to create scour pool habitat. We investigated local scour pools created by paired porous obstructions using laboratory experiments. To examine the influence of porous obstructions on local scour depths and volumes, various densities in the porous obstructions, ratio of obstruction width to channel width and submergence ratio were evaluated. A local scour pool developed when the flow blockage (product of density in the porous obstructions and ratio of obstruction width to channel width) and the ratio of the obstruction width to channel width were ≥5.0 and ≥0.4, respectively. The depth of the scour pool increased with increasing flow blockage, while scour depth reduced as the submergence ratio increased. The scoured volume had a strong relationship with the scour depth around the porous obstructions. Results of the predictive equations were considered reliable for estimating the maximum scour depth and scoured volume around porous obstructions in clear-water conditions.

Description: Water, Vol. 10, Pages 356: Crop Upgrading Strategies and Modelling for Rainfed Cereals in a Semi-Arid Climate—A Review Water doi: 10.3390/w10040356 Authors: Festo Silungwe Frieder Graef Sonoko Bellingrath-Kimura Siza Tumbo Frederick Kahimba Marcos Lana Spatiotemporal rainfall variability and low soil fertility are the primary crop production challenges facing poor farmers in semi-arid environments. However, there are few solutions for addressing these challenges. The literature provides several crop upgrading strategies (UPS) for improving crop yields, and biophysical models are used to simulate these strategies. However, the suitability of UPS is limited by systemization of their areas of application and the need to cope with the challenges faced by poor farmers. In this study, we reviewed 187 papers from peer-reviewed journals, conferences and reports that discuss UPS suitable for cereals and biophysical models used to assist in the selection of UPS in semi-arid areas. We found that four UPS were the most suitable, namely tied ridges, microdose fertilization, varying sowing dates, and field scattering. The DSSAT, APSIM and AquaCrop models adequately simulate these UPS. This work provides a systemization of crop UPS and models in semi-arid areas that can be applied by scientists and planners.

Description: Water, Vol. 10, Pages 223: Responses of Bed Morphology to Vegetation Growth and Flood Discharge at a Sharp River Bend Water doi: 10.3390/w10020223 Authors: Taeun Kang Ichiro Kimura Yasuyuki Shimizu In this study, we conducted simulations using a two-dimensional, depth-averaged river flow and river morphology model to investigate the effect of vegetation growth and degree of flow discharge on a shallow meandering channel. To consider the effects of these factors, it was assumed that vegetation growth stage is changed by water flow and bed erosion. The non-uniformity of the vegetation growth was induced by the non-uniform and unsteady profile of the water depth due to the irregular shape of the bed elevation and the unsteady flow model reliant on hydrographs to evaluate three types of peak discharges: moderate flow, annual average maximum flow, and extreme flow. To compare the effects of non-uniform growing vegetation, the change in channel patterns was quantified using the Active Braiding Index (ABI), which indicates the average number of channels with flowing water at a cross section and the Bed Relief Index (BRI), which quantifies the degree of irregularity of the cross-sectional shape. Two types of erosion were identified: local erosion (due to increased flow velocity near a vegetation area) and global erosion (due to the discharge approaching peak and the large depth of the channel). This paper demonstrated that the growth of vegetation increases both the ABI and BRI when the peak discharge is lower than the annual average discharge, whereas the growth of vegetation reduces the BRI when the peak discharge is extreme. However, under extreme discharge, the ABI decreases because global erosion is dominant. The conclusions from this study help to deepen the understanding of the interactions between curved river channels and vegetation.

Description: This study describes morphological changes with a vegetation patch using both laboratory experiments and numerical simulations. Four experimental cases are carried out with two patch densities and without a patch. The patch is constructed with emergent cylinders of 5 mm in a staggered array and it is located at the mid-channel. A 2D depth-averaged model is proposed to simulate flow and morphological change with vegetation. For non-vegetation cases, channel widening occurs with bank erosion, whereas the added patch in open channels causes significant bank erosion opposite and downstream of the patch, and failed sediment is deposited downstream of the patch. Local scour is observed near the lateral edge of the patch, and its depth increases with increasing patch density. Small-scale scour occurs in the immediate vicinity of cylinders within the patch due to increased turbulence. Averaged channel width increases with increasing discharge, channel slope and the patch density. Comparisons with experimental data show the numerical model predicts spatial patterns of erosion and deposition as well as lateral bank erosion caused by the vegetation patch reasonably well, so could be a useful tool for the future design and assessment of river restoration works involving vegetation.

Description: Recent extreme weather events like the August 2016 flood disaster have significantly affected farmland in mid-latitude regions like the Tokachi River (TR) watershed, the most productive farmland in Japan. The August 2016 flood disaster was caused by multiple typhoons that occurred in the span of two weeks and dealt catastrophic damage to agricultural land. This disaster was the focus of our flood model simulations. For the hydrological model input, the rainfall data with 0.04° grid space and an hourly interval were provided by a regional climate model (RCM) during the period of multiple typhoon occurrences. The high-resolution data can take account of the geographic effects, hardly reproduced by ordinary RCMs. The rainfall data drove a conceptual, distributed rainfall–runoff model, embedded in the integrated flood analysis system. The rainfall–runoff model provided discharges along rivers over the TR watershed. The RCM also provided future rainfall data with pseudo-global warming climate, assuming that the August 2016 disaster could reoccur again in the late 21st century. The future rainfall data were used to conduct a future flood simulation. With bias corrections, current and future flood simulations showed the potential inundated areas along riverbanks based on flood risk levels. The crop field-based agricultural losses in both simulations were estimated. The future cost may be two to three times higher as indicated by slightly higher simulated future discharge peaks in tributaries.

Description: East Asian regions in the North Pacific have recently experienced severe riverine flood disasters. State-of-the-art neural networks are currently utilized as a quick-response flood model. Neural networks typically require ample time in the training process because of the use of numerous datasets. To reduce the computational costs, we introduced a transfer-learning approach to a neural-network-based flood model. For a concept of transfer leaning, once the model is pretrained in a source domain with large datasets, it can be reused in other target domains. After retraining parts of the model with the target domain datasets, the training time can be reduced due to reuse. A convolutional neural network (CNN) was employed because the CNN with transfer learning has numerous successful applications in two-dimensional image classification. However, our flood model predicts time-series variables (e.g., water level). The CNN with transfer learning requires a conversion tool from time-series datasets to image datasets in preprocessing. First, the CNN time-series classification was verified in the source domain with less than 10% errors for the variation in water level. Second, the CNN with transfer learning in the target domain efficiently reduced the training time by 1/5 of and a mean error difference by 15% of those obtained by the CNN without transfer learning, respectively. Our method can provide another novel flood model in addition to physical-based models.

Description: Investigating the influence of sea surface temperatures (SSTs) on seasonal rainfall is a crucial factor for managing Ethiopian water resources. For this purpose, SST and rainfall data were used to study a wide range of inhomogeneous areas in Ethiopia with uneven distribution of rainfall for both summer (1951–2015) and spring (1951–2000) seasons. Firstly, a preliminary subdivision of rainfall grid points into zones was applied depending on spatial homogeneity and seasonality of rainfall. This introduced new clusters, including nine zones for summer rainfall peak (July/August) and five zones for spring rainfall peak (April/May). Afterward, the time series for each zone was derived by calculating the rainfall averaged over grid points within the zone. Secondly, the oceanic regions that significantly correlated with the Ethiopian rainfall were identified through cross-correlations between rainfalls averaged over every homogeneous zone and the monthly averaged SST. For summer rainfall as a main rainy season, the results indicated that the Gulf of Guinea and southern Pacific Ocean had a significant influence on rainfall zones at a lag time of 5–6 and 6–7 months. Besides, for summer rainfall zones 8 and 9 at lag time 5–6 months, the common SST regions of the southern Pacific Ocean showed the opposite sense of positive and negative correlations. Thus, the difference in SSTs between the two regions was more strongly correlated (r ≥ 0.46) with summer rainfall in both zones than others. For the spring season, the results indicated that SST of the northern Atlantic Ocean had a strong influence on spring rainfall zones (3 and 5) at a lag time 6–7 months, as indicated by a significant correlation (r ≥ −0.40). Therefore, this study suggests that SSTs of southern Pacific and northern Atlantic oceans can be used as effective inputs for prediction models of Ethiopian summer and spring rainfalls, respectively.