Quantification of Amu River Riverbank Erosion in Balkh Province of Afghanistan during 2004–2020

In this study, we propose quantifying the Amu River riverbank erosion with the modelled river discharge in Kaldar District, Balkh Province of Afghanistan from 2004 to 2020. We propose a framework synergizing multi-source information for modelling the erosion area based on three components: (1) river discharge, (2) river width, and (3) erosion area. The total river discharge for the watershed shared by Afghanistan and Tajikistan was modelled using hydrological parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) data through multivariate linear regression with ground station data. The river width was determined manually using the Normalized Difference Water Index (NDWI) derived from Landsat data. The riverbank erosion area was derived from the digital shoreline analysis using the NDWI. The digital shoreline analysis showed that, between 2008 and 2020, the average riverbank erosion area in Kaldar District is about 5.4 km2 per year, and, overall, 86.3 km2 during 2004–2020 due to flood events. The significantly higher land loss events occurred at 10 km2 bank erosion during the years 2008–2009 and 2015–2016, and 19 km2 peak erosion occurred during 2011–2012. A linear relation between the erosion area with respect to the discharge intensity and the specific stream power was observed with an R2 of 0.84 and RMSE of 1.761 for both

ナンシツFRPライニングコウホウ ニ ヨル カイスイロ ノ ソドケイスウ

老朽化水路の補修に用いる軟質FRPライニング板を実験用開水路に設置し,粗度係数の測定を行った。その結果,補修水路の粗度係数は0.0094であり,新設コンクリート水路に勝る通水機能を有することが明らかになった。また,粗度係数は,流速,径深との関係よりも,動水勾配との相関が最も大きかったことから,勾配の変化に対して粗度係数も変化することが示された。一方,流量の指標であるレイノルズ数と粗度係数の関係を検討したところ,レイノルズ数の増加に伴って粗度係数の変動が大きくなる傾向を示した。以上のことから,粗度係数は,流況や現場の地形要素に影響を受けて変化することから,補修板による水路補修を考える場合,これらの指標をふまえて適切な粗度係数を適用する必要がある。A flexible fiber-reinforced plastic lining that is used for repairing deteriorated water channel was installed in an experimental water channel to examine the effect of such repair on flow in the channel. Manning\u27s roughness coefficient, which is an indicator of the smoothness of flow, was used in the examination. The measured roughness coefficient of the repaired channel was 0.0094, which is lower than in a newly constructed concrete channel. This shows that the water flow after such a repair is smoother than in a newly constructed concrete channel. The influence of flow velocity, channel depth and hydraulic gradient on the roughness coefficient was examined. Changes in the roughness coefficient were found to correlate most closely with changes in the hydraulic gradient, i.e., channel gradient has the greatest influence on the smoothness of the water flow. The relationship between roughness coefficient and Reynolds number (an index of discharge) was examined. The greater is the Reynolds number, the greater is the dispersion in roughness coefficient for different discharges. This shows that the roughness coefficient is influenced by topography and flow regime at repair sites. When determining the roughness coefficient for a repair site, it is necessary to consider the topography and flow regime

ハイブリッドガタヒーティングソウチ ノ カイハツ ト ロードヒーティングヘノテキヨウセイ ニ カンスル ケンキュウ

積雪寒冷地では,歩道を含む道路の雪対策として,幾つかの種類のロードヒーティングが行われているが,運用に際してはランニングコストが安くともイニシャルコストが高い,またはその逆といった財政的な要因があるため,広く普及していないのが現状である。本研究では,温泉排水を利用することを前提に,安価な金属パイプに液化ガスを封入した簡易なハイブリッド型ヒーティング装置を製作し,室内での昇温実験および融雪実験を行った。その結果,封入する液化ガスとして代替フロンHFC-R407Cおよび液化石油ガスLPGの2種類について検討したところ,HFC-R407Cの昇温効果が優れていたこと,金属パイプを蛇行させることでパイプ温度が距離によらず均一になったこと,舗装体内に埋設するにあたっては,加熱部は放熱部よりも下方に位置し,放熱部は2°以上の勾配を持たせて設置させる必要があること,熱源に温水を用いることでロードヒーティングに必要な融雪熱量が得られることがわかった。Some kinds of road heating systems are applied as one of the snow disaster-countermeasures for roads including side-walks in snowy areas. However, the road heating system is not used widely because of the initial cost. The running cost is low but the initial cost is very high. In this study, on the assumption that the drainage water from hot spring is applicable for road heating, a simple hybrid heating device with metal pipes in which liquefied gas was infused was developed, and the temperature rising test and the snow melting test using the hybrid heating device were carried out in a laboratory. As a result, it was confirmed that the heating device developed in this study had enough snow melting ability for road heating

ハイブリッドガタヒーティングソウチ ノ カイハツ ト ロードヒーティングヘノテキヨウセイ ニ カンスル ケンキュウ

積雪寒冷地では,歩道を含む道路の雪対策として,幾つかの種類のロードヒーティングが行われているが,運用に際してはランニングコストが安くともイニシャルコストが高い,またはその逆といった財政的な要因があるため,広く普及していないのが現状である。本研究では,温泉排水を利用することを前提に,安価な金属パイプに液化ガスを封入した簡易なハイブリッド型ヒーティング装置を製作し,室内での昇温実験および融雪実験を行った。その結果,封入する液化ガスとして代替フロンHFC-R407Cおよび液化石油ガスLPGの2種類について検討したところ,HFC-R407Cの昇温効果が優れていたこと,金属パイプを蛇行させることでパイプ温度が距離によらず均一になったこと,舗装体内に埋設するにあたっては,加熱部は放熱部よりも下方に位置し,放熱部は2°以上の勾配を持たせて設置させる必要があること,熱源に温水を用いることでロードヒーティングに必要な融雪熱量が得られることがわかった。Some kinds of road heating systems are applied as one of the snow disaster-countermeasures for roads including side-walks in snowy areas. However, the road heating system is not used widely because of the initial cost. The running cost is low but the initial cost is very high. In this study, on the assumption that the drainage water from hot spring is applicable for road heating, a simple hybrid heating device with metal pipes in which liquefied gas was infused was developed, and the temperature rising test and the snow melting test using the hybrid heating device were carried out in a laboratory. As a result, it was confirmed that the heating device developed in this study had enough snow melting ability for road heating

ECOSYSTEM SERVICE ASSESSMENT IN AGRICULTURAL WATERSHED BY USING TOPMODEL

In Millennium Ecosystem Assessment established by the United Nations, theecosystem services (ES) provide benefits for human life as well as theenvironment. There is “regulating services” among all the supporting services. As aregulatory service, forests alleviate the flood risk after heavy rain by storingrainfall temporarily into forestlands and prevent the sudden increase in riverdischarge. The purpose of this research is to develop a hydrological modelling toassess this service in a watershed where consists of not only forestland but alsograssland. TOPMODEL is applied for the quantification. This model was inventedto forecast river discharge in watersheds where the land use is uniform. However,the model has not been applied to a watershed where agricultural and forest areaare mixed in Japan. This research aimed to develop TOPMODEL to apply to suchcomplexed land use. Because the targeted watershed is consisted of two land-usetypes, TOPMODEL was applied in each grassland and forestland. It predicted theriver discharge by combining the predicted discharge from the different types ofland calculated by TOPMODEL. The result confirmed that by developing themodel, it was able to assess the water discharge from the both grassland andforestland in a watershed. The developed model also showed the betterreproducibility of river-discharge prediction than the conventional TOPMODEL.In addition, it clarified that the forestland stores more water than grassland into theground. Therefore, the effect of flood control which is the regulatory service of ESwas assessable through the developed model

A Comparative Evaluation of Lumped and Semi-Distributed Conceptual Hydrological Models: Does Model Complexity Enhance Hydrograph Prediction?

The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of ‘Nash-Sutcliffe efficiency’ and ‘RMSE-observations standard deviation ratio’ indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL’s better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment

A Comparative Evaluation of Lumped and Semi-Distributed Conceptual Hydrological Models: Does Model Complexity Enhance Hydrograph Prediction?

The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of ‘Nash-Sutcliffe efficiency’ and ‘RMSE-observations standard deviation ratio’ indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL’s better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment

Optimization of Ground Control Point Distribution for Unmanned Aerial Vehicle Photogrammetry for Inaccessible Fields

Ground control point (GCP) is an important calibration factor when correcting position information during unmanned aerial vehicle (UAV) remote sensing. Studies of the optimal number and distribution shape of GCPs have been conducted worldwide in recent years. However, when conducting surveys at houses, construction sites, farming lands, forests, and some other locations, it is both difficult and destructive to install GCP inside the subject area. In many cases, it is only possible to install GCP at the outer edge around the area. Therefore, this study aims to suggest the optimal GCP distribution pattern, which can provide the highest accuracy, when only the outer edge of a particular area is available. In this research, 88 GCP patterns have been validated and compared at an 18 ha farm. Results show that the patterns with GCPs distributed evenly around the field provided the best calibration (RMSE = 0.15 m). If this kind of pattern is not achievable because of obstructions, patterns with GCPs distributed evenly around half of the field or forming an evenly distributed triangle can provide moderate accuracy (RMSE = 0.18 m and 0.43 m, respectively). Patterns with GCPs forming a straight line yielded the worst accuracy (RMSE = 2.10 m). This shows that GCP distributions of a two-dimensional shape, even if the surrounding area is small, are better calibrated than a long, straight line. These results strongly suggest that appropriate GCP distribution patterns in the study areas will provide satisfactory accuracy for constructing integrated monitoring systems of diverse resources

Optimization of Ground Control Point Distribution for Unmanned Aerial Vehicle Photogrammetry for Inaccessible Fields

Ground control point (GCP) is an important calibration factor when correcting position information during unmanned aerial vehicle (UAV) remote sensing. Studies of the optimal number and distribution shape of GCPs have been conducted worldwide in recent years. However, when conducting surveys at houses, construction sites, farming lands, forests, and some other locations, it is both difficult and destructive to install GCP inside the subject area. In many cases, it is only possible to install GCP at the outer edge around the area. Therefore, this study aims to suggest the optimal GCP distribution pattern, which can provide the highest accuracy, when only the outer edge of a particular area is available. In this research, 88 GCP patterns have been validated and compared at an 18 ha farm. Results show that the patterns with GCPs distributed evenly around the field provided the best calibration (RMSE = 0.15 m). If this kind of pattern is not achievable because of obstructions, patterns with GCPs distributed evenly around half of the field or forming an evenly distributed triangle can provide moderate accuracy (RMSE = 0.18 m and 0.43 m, respectively). Patterns with GCPs forming a straight line yielded the worst accuracy (RMSE = 2.10 m). This shows that GCP distributions of a two-dimensional shape, even if the surrounding area is small, are better calibrated than a long, straight line. These results strongly suggest that appropriate GCP distribution patterns in the study areas will provide satisfactory accuracy for constructing integrated monitoring systems of diverse resources

Assessment of Three Automated Identification Methods for Ground Object Based on UAV Imagery

Identification and monitoring of diverse resources or wastes on the ground is important for integrated resource management. The unmanned aerial vehicle (UAV), with its high resolution and facility, is the optimal tool for monitoring ground objects accurately and efficiently. However, previous studies have focused on applying classification methodology on land use and agronomy, and few studies have compared different classification methods using UAV imagery. It is necessary to fully utilize the high resolution of UAV by applying the classification methodology to ground object identification. This study compared three classification methods: A. NDVI threshold, B. RGB image-based machine learning, and C. object-based image analysis (OBIA). Method A was the least time-consuming and could identify vegetation and soil with high accuracy (user’s accuracy > 0.80), but had poor performance at classifying dead vegetation, plastic, and metal (user’s accuracy < 0.50). Both Methods B and C were time- and labor-consuming, but had very high accuracy in separating vegetation, soil, plastic, and metal (user’s accuracy ≥ 0.70 for all classes). Method B showed a good performance in identifying objects with bright colors, whereas Method C showed a high ability in separating objects with similar visual appearances. Scientifically, this study has verified the possibility of using the existing classification methods on identifying small ground objects with a size of less than 1 m, and has discussed the reasons for the different accuracy of the three methods. Practically, these results help users from different fields to choose an appropriate method that suits their target, so that different wastes or multiple resources can be monitored at the same time by combining different methods, which contributes to an improved integrated resource management system