Morphometric analysis for flood flow formation feature identification (on example of Ulaanbaatar agglomeration)

Water flows with significant flow rate feature a high destructive force and can lead to catastrophic consequences. Fluvial processes caused by uneven distribution of rain precipitation over the area pose risks to the developed inland foothill territories. The purpose of this study is to carry out a quantitative morphometric analysis of the territory in order to identify the formation features of flood flows. The analysis and ranking of catchment basins are performed using a basin approach. On the basis of SRTM images and the use of stock cartographic material in the GIS program the authors have built specialized electronic maps that allow to obtain quantitative parameters reflecting the morphometry of the basins under analysis including basin geometry, drainage network and terrain relief. On example of the Ulaanbaatar agglomeration territory it is shown how initial morphometric parameters of basins and watercourses (length, width, area, perimeter, erosion dissection, drainage network density, terrain relief coefficient, Melton coefficient, etc.) form the features of flood flow. For developed territories, the initial data on the catchment basin morphometry constitute the basis for compilation of specialized maps to be used in planning and construction. The combination of morphometric indicators on the territory of the Ulaanbaatar agglomeration indicates that there is possibility of large flood formation and development of dangerous mudstone flows in some catchment basins.

The Use of Artificial Neural Network and Advanced Statistics to Model Sediment Yield on a Large Scale: Example of Morocco

Morocco ranks among countries with the greatest achievements in the field of dams in Africa but is affected by the sedimentation phenomenon due to soil erosion in upstreams. The assessment of Sediment Yield (SY) and Suspended Sediment Yield (SSY) remains a challenging global issue, especially in Morocco, characterized by a great diversity of morphological, climatic, and vegetation cover. The main objective of this paper was to perform advanced statistics and artificial neural networks (ANN) in order to understand the spatial distribution of sediment yield and the factors most controlling it, including factors of the RUSLE model (Revised Universal Soil Loss Equation). In order to produce a model able to assess SY, we collected and analyzed extensive data of most variables that can be affecting SY using 42 catchments of the biggest and important dams of Morocco. Statistical analysis of the studied watersheds shows that SY is mainly related to the watershed area and the length of the drainage network. On the other hand, the SSY is higher in watersheds where gully erosion is abundant and lower in areas with no soil horizon. The SSY is mainly related to the altitude, aridity index, sand fraction, and drainage network length. In front of the complexity of preserving this phenomenon, the ANN was applied and gave very good satisfactory results in predicting the SSY (NSE=0.93, R2=0.93).

Flood Hazard Zonation Using an Artificial Neural Network Model: A Case Study of Kabul River Basin, Pakistan

Floods are the most frequent and destructive natural disasters causing damages to human lives and their properties every year around the world. Pakistan in general and the Peshawar Vale, in particular, is vulnerable to recurrent floods due to its unique physiography. Peshawar Vale is drained by River Kabul and its major tributaries namely, River Swat, River Jindi, River Kalpani, River Budhni and River Bara. Kabul River has a length of approximately 700 km, out of which 560 km is in Afghanistan and the rest falls in Pakistan. Looking at the physiography and prevailing flood characteristics, the development of a flood hazard model is required to provide feedback to decision-makers for the sustainability of the livelihoods of the inhabitants. Peshawar Vale is a flood-prone area, where recurrent flood events have caused damages to standing crops, agricultural land, sources of livelihood earnings and infrastructure. The objective of this study was to determine the effectiveness of the ANN algorithm in the determination of flood inundated areas. The ANN algorithm was implemented in C# for the prediction of inundated areas using nine flood causative factors, that is, drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use. For the preparation of spatial geodatabases, thematic layers of the drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use were generated in the GIS environment. A Neural Network of nine, six and one neurons for the first, second and output layers, respectively, were designed and subsequently developed. The output and the resultant product of the Neural Network approach include flood hazard mapping and zonation of the study area. Parallel to this, the performance of the model was evaluated using Root Mean Square Error (RMSE) and Correlation coefficient (R2). This study has further highlighted the applicability and capability of the ANN in flood hazard mapping and zonation. The analysis revealed that the proposed model is an effective and viable approach for flood hazard analysis and zonation.

Water Resources and Management in Gori Ganga Watershed, Kumaun Himalaya by Using Remote Sensing and GIS

Uttarakhand Himalaya has been famous for its water resources (source for many rivers), forest diversity, unique wildlife, rich traditional culture, tribal culture and sacred Hindu’s shrine (i.e. Gangotri, Yamnotri, Kedarnath and Badrinath). The present study aims to assess the status of water resources in the Gori Ganga watershed. Water resources and their management were collected through field visit, use of Global Position System (GPS) and various methods (include questionnaire, personal interviews, direct interaction and group discussion with the villagers). Study explores the ability of Digital Elevation Model (DEM) in delineating watershed and drainage network of the Gori Ganga River basin. Gori Ganga watershed is laying in Eastern Kumaon Himalaya with great utility of water resources in socio-economic development for livelihood where the settlements are situated in valleys to high altitude. Gori Ganga drainage network i.e. Ralam, Mandakani and Bona gad is glacial fed river and these entire Rivers’s water received annually from glaciers which are very useful for development of villages, towns and hydro power stations in the watershed region. Study explores some traditional water resources (Glacier, streams, springs/Dhare/Naule, lakes/Kund/Taals and drainage network) and uses of water resources for traditional uses i.e. Gharat (watermill), drinking water, hydro power production, agriculture irrigation, fisheries and animal husbandry etc. in the study area. Keywords: Water Resource, Management, Socio and Economic Development, Remote Sensing and GIS.

Inventory and Assessment of the Geomorphosites in Central Cyclades, Greece: The Case of Paros and Naxos Islands

The Cycladic landscape is characterized by landforms of natural beauty and rarity. Landforms resulting from differential erosion, weathering, tectonics, drainage network, sea level changes, and depositional processes can contribute to the development of geotourism in the area. This can be achieved by supporting conservation, protection and promotion of the geo-environment and nature, educating students, residents, and visitors. The aim of this work is to develop an inventory of the main geomorphosites of Paros and Naxos islands by assessing their scientific and additional values, using qualitative and quantitative criteria. Our results show that, besides the high scientific interest of the 75 geomorphosites, most are also characterized by a high ecological value and can potentially lead to a significant increase in the islands’ tourism. The results of this work aim at raise awareness on the geomorphological heritage of central Cyclades and provide a basis for their promotion, protection, and management.

ANALYSIS AND EVALUATION OF THE DRAINAGE NETWORK SYSTEM IN THE HOUSING AREA OF VILA RIZKI ILHAMI 2 SAWANGAN, DEPOK-WEST JAVA

<p>The impact that occurs from the rampant development of residential areas will certainly make the volume of surface water flow or run off become large. Drainage is a system created to deal with the problem of excess water flow that is above the surface of the earth, some of the things that cause excess water are caused by high water intensity and the long duration of rain. In this study, the problem that occurred was in the drainage network in the residential area of Vila Rizki Ilhami 2 Sawangan, which was a transfer of land functions from infiltration land into a residential area. Evaluation that must be done is covering hydrological analysis and hydraulics analysis to get the amount of flood discharge plan that will be used to analyze the capacity of the planned channel so that no flooding occurs at the location of the settlement area when the settlement is built, recommendations for drainage system design and determine the size of the river dimension / size / times that should be made when accommodating water discharge during maximum rain so that the flood control system can be well integrated. With 3 methods of calculating rainfall, the method of calculation is selected using the gumbel method which is SNI (Indonesian National Standard) with a return period of 2 years, 5 years and 10 years. From the evaluation obtained is to add height height or free board to accommodate flood discharge plan.</p>

Factors influencing physicochemical characteristics of faecal sludge in Phnom Penh, Cambodia

Comprehensive knowledge of faecal sludge characteristics is needed for sludge management planning, but it is lacking for the city of Phnom Penh, Cambodia. Thus, this study characterised physicochemical properties of faecal sludge from households in Phnom Penh and related these to sludge containment unit type, unit age, connectedness to the urban drainage network, type of wastewater captured, watertight containment units, number of users, and emptying practices. In total, 194 faecal sludge samples collected during containment unit emptying were analysed for physicochemical parameters. Information on containment units was collected in a survey of emptiers and users. Mean values of faecal sludge chemical parameters were found to be slightly lower than previously reported values for low-/middle-income countries, whereas physicochemical properties were within similar ranges. The main factor influencing organic matter content in faecal sludge was containment unit connection to the urban drainage network, whereas emptying practice and capture of only blackwater affected nutrient levels. The concentrations of nutrients and organic pollutants greatly exceeded Cambodian discharge standards for wastewater. This causes environmental impacts, so treatment is needed before discharge. The faecal sludge characteristics and influencing factors identified here can serve as a baseline for sanitation stakeholders planning faecal sludge management systems in Phnom Penh and similar cities.

Evolution of Surface Drainage Network for Spoil Heaps under Simulated Rainfall

Spoil heaps laid from the infrastructure building sites or the mining sites are confoundedly prone to accelerated soil erosion and inducing debris flows on extreme rainfall occasion, thus threatening water quality and personal safety. In present study, the roughness and drainage network evolution of the loess spoil heap (a 33° slope gradient) were investigated via indoor simulation experiment under three rainfall intensities (60, 90, and 120 mm/h). A detailed scan of the slope using laser scanner, topographic analysis based on ArcGIS software, and statistical analyses were the main methods utilized in the study. The results showed that surface roughness increased with cumulative rainfall. For three rainfall intensity treatments, the proneness of shallow landslide under 90 mm/h intensity resulted in the largest roughness. The drainage density and stream frequency of the spoil heap slope both decreased with cumulative rainfall and negatively correlated with surface roughness, which indicated the convergence of the drainage network. Meanwhile, the individual flow paths presented an increasing sinuosity and a decreasing gradient with cumulative rainfall. However, drainage network features varied in a less marked degree during different rainfall intensities, showing comparable fractal dimensions of 1.350–1.454, 1.305–1.459, and 1.292–1.455 for the three rainfall intensities. Evaluating the response of four hydrodynamic characteristics of runoff to the drainage network evolution, stream power was found to be most sensitive. The linearity of the relationships between stream power and drainage density and that between stream sinuosity and gradient were estimated to have R2 between 0.961 and 0.979.