scholarly journals A Hybrid Stochastic-ANN Approach for Flow Partitioning in the Okavango Delta of Botswana

2013 ◽  
Vol 16 (1) ◽  
pp. 68-79
Keyword(s):  
River Flow ◽  
Moving Average ◽  
River System ◽  
Flood Pulse ◽  
Okavango Delta ◽  
Single Output ◽  
Main River ◽  
Main River Channel ◽  
Input Multiple Output ◽  
Stochastic Forecasting

<p>Since a spectrum of hydrological and geomorphological conditions produce flood pulse environment in a riverine or a deltaic system, it is essential to have the knowledge on spatial and temporal distributions of river flow and dependent processes for environmental flow requirements, ecosystem maintenance, water resources management, and hydrological forecasting among others. Such systems being complex as the exchange of flows between the main channel and the flood plains are not well understood, flow partitioning dynamics between the various channels on large water bodies are often difficult to represent even with sophisticated models. In view of this, an attempt has been made to apply a short-term stochastic forecasting model-an Auto Regressive Integrated Moving Average (ARIMA) aided by Artificial Neural Networks (ANNs) to partition flows into the downstream tributaries, viz.: Lopis and Gadikwe channels from the Khiandiandavhu-Maunachira (K-M) Junction Junction (the main river channel) river system of the iconic Okavango delta in Botswana. As such, observed monthly flow data between October 2005 and September 2008 at the K-M Junction, and the two downstream tributaries were used to test the performance of these hybrid models for the complex deltaic system. It was found that the partitioned flows at Lopis and Gadikwe agree very well with observations when using a Single Input Multiple Output (SIMO) ANN (i.e. an inverse variant of the widely used Multi Input Single Output (MISO) ANN architecture) and an ARIMA (1,1,1) model. The Mean Squared Errors (MSEs) in the forecasts were also minimal, thus giving some hope on the use of such a hybrid mode for the rest of the branched river networks of the whole Okavango delta.</p>

High prevalence of non-native fish species in a remote region of the Mamberamo River, Indonesia

2020 ◽  
Vol 26 (3) ◽  
pp. 293
Author(s):  
Arif Wibowo ◽  
Dwi Atminarso ◽  
Lee Baumgartner ◽  
Anti Vasemagi
Keyword(s):  
Native Species ◽  
River System ◽  
New Guinea ◽  
Current Status ◽  
Native Fish ◽  
Fish Diversity ◽  
Main River ◽  
Main River Channel ◽  
High Prevalence ◽  
Major River

Indonesian freshwater fish diversity is threatened by human activities such as logging, land clearing, pollution and introduction of non-native species. The latter may pose serious threats to endemic freshwater fauna even in relatively pristine and isolated habitats. One such area, West Papua in the island of New Guinea, is one of the least studied regions in the world and a biodiversity hotspot. The Mamberamo River contains the highest proportion of non-native fish compared to other major river systems in New Guinea. To document this, we conducted a field study to validate and further temporally characterise the fish biodiversity to ascertain its current status. Since the last ichthyological survey 15 years ago, we detected two additional non-native species (Leptobarbus melanopterus and Oreochromis niloticus) that have established in the river system. Moreover, our survey revealed that non-native fish are extremely common in the mid reaches of the Mamberamo River, comprising 74% of total catch, with non-native Barbonymus gonionotus (family Cyprinidae) now established as the dominant species. The biomass of non-native B. gonionotus now exceeds that of all native fish combined in the main river channel. These results highlight the serious threat of invasive species in remote regions that support high levels of endemic biodiversity. Plans for containment, prevention through education programmes, and management are urgently required.

scholarly journals Simulating stream flow over data sparse areas – an application of internet based data

2011 ◽  
Vol 8 (6) ◽  
pp. 11015-11037
Author(s):  
M. T. Vu ◽  
S. V. Raghavan ◽  
S. Y. Liong
Keyword(s):  
Hydrological Modeling ◽  
River Flow ◽  
Shuttle Radar Topography Mission ◽  
Observation Data ◽  
Food And Agriculture ◽  
Internet Resources ◽  
Modeling Studies ◽  
Food And Agriculture Organization ◽  
Main River ◽  
Main River Channel

Abstract. Many hydrological modeling studies suffer from lack of robust station observed data, mainly rainfall and discharge. Where such a dearth of data exists, detailed modeling studies in estimating and assessing change in water resources become difficult when models cannot be compared against recorded observations. In addition, some river basins exist along trans-boundaries of two or more countries that problems in data sharing among them add to the difficulties in such modeling studies. Nevertheless, with the advancement in the global internet resources, access to such data has become easy. Whether such internet based data are good substitutes for station data can be ascertained only after performing some modeling research. To this end, this paper describes a hydrological modeling study that simulates the river flow of the Da River across the trans-boundary regions of China and Vietnam over a 11 yr period from 1971 to 1982. Globally available observation data used in this study include topography (from SRTM – Shuttle Radar Topography Mission), land use (from GLCC – Global Land Cover Characterization), soil (from FAO – Food and Agriculture Organization), precipitation (from APHRODITE – Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation) and temperature (from GHCN2 – modified of Global Historical Climatology Network version 2). The study employs a hydrological model to recreate the natural flow without dam(s) built across the main river channel. The results of the study are promising and provide a wide scope to utilize internet based data for further research. This also has implications in the context of climate change applications.

scholarly journals Problems of Shapour River Salinity Rising Over Recent Prolonged Streamflow Reduction Period and Solutions of River Salinity Management: An Originally Freshwater River Intensively Salinized by Natural Salinity Sources

2021 ◽  
Author(s):  
Jahanshir Mohammadzadeh-Habili ◽  
Davar Khalili ◽  
Shahrokh Zand-Parsa ◽  
Abdoreza Sabouki ◽  
Ali Dindarlou ◽  
...  
Keyword(s):  
River Flow ◽  
River System ◽  
Irrigation Season ◽  
Salt Accumulation ◽  
Salinity Fluctuation ◽  
Main River ◽  
Major River ◽  
Seasonal Time Scale ◽  
Salinity Management ◽  
Freshwater River

Abstract The Shapour river with catchment area of 4254 km2 is a major river system in southern Iran. While the upstream river flow (the upper Shapour river) is fresh, it becomes extremely salinized at the downstream confluence of Shekastian salty tributary and the entering nearby Boushigan brine spring. The river then passes through the Khesht plain and finally discharges into the Raeisali-Delvari storage dam, which went into operation in 2009. Over the 2006–2019 period, reduced precipitation and over-utilization of freshwater resources resulted in ~ 72% streamflow reduction in the Shapour river. Consequently, the ratios of unused salty/brine water of Shekastian tributary and Boushigan spring to fresh-outflow of the upper Shapour river increased by ~ 3 times and river salinity fluctuation domain at the Khesht plain inlet dramatically increased from 2.1-4.0 dS m− 1 to 3.7–26.0 dS m− 1. It also resulted in disappearance of most river aquatic species and caused major economic damages in the middle Shapour river. On the seasonal time-scale, consecutive processes of salt accumulation during irrigation season of the Khesht plain date orchards and then salt drainage during rainy season have adjusted salinity fluctuation domain from 3.7–26.0 dS m− 1 at the plain inlet to 5.2–8.9 dS m− 1 at the plain outlet. In the lower Shapour river, storage/mixing of fresh/salty inflow waters in the Raeisali-Delvari reservoir has adjusted strong salinity fluctuation domain from 0.9–10.7 dS m− 1 at the reservoir inlet to 3.6–5.5 dS m− 1 at the reservoir outlet. Success of the Raeisali-Delvari reservoir for salinity adjustment is due to its suitable location on the Shapour river, by being situated on downstream of all of the main river tributaries with natural saline/fresh sources of water. Therefore, construction of storage dam on proper site in conjunction with controlled freshwater utilization are viewed as effective measures for salinity management of subjected rivers to natural salinity sources.

scholarly journals Vulnerability of groundwater resources to interaction with river water in a boreal catchment

2015 ◽  
Vol 12 (2) ◽  
pp. 2435-2476 ◽  
Author(s):  
A. Rautio ◽  
A.-L. Kivimäki ◽  
K. Korkka-Niemi ◽  
M. Nygård ◽  
V.-P. Salonen ◽  
...  
Keyword(s):  
Water Intake ◽  
Groundwater Resources ◽  
River System ◽  
River Basin Management ◽  
Low Flow ◽  
Interaction Sites ◽  
Main River ◽  
Main River Channel ◽  
Longitudinal Temperature ◽  
Groundwater Surface Water Interaction

Abstract. A low altitude aerial infrared (AIR) survey was conducted to identify hydraulic connections between aquifers and rivers, and to map spatial surface temperature patterns along boreal rivers. In addition, the stable isotopic compositions (δ18O, δD), dissolved silica (DSi) concentrations and electrical conductivity of water in combination with AIR data were used as tracers to verify the observed groundwater discharge into the river system in a boreal catchment. The results of AIR surveys and hydrogeochemical studies performed in the boreal catchment are presented. Based on low temperature anomalies in the AIR survey, around 370 groundwater–surface water interaction sites were located along the main river channel and its tributaries (203 km altogether). On the basis of AIR survey, the longitudinal temperature patterns of the studied rivers differed noticeably. The stable isotopes and DSi composition revealed major differences between the studied rivers. The interaction locations identified in the proximity of 12 municipal water intake plants during the low-flow seasons should be considered as potential risk areas for water intake plants during flood periods (groundwater quality deterioration due to bank infiltration), and should be taken under consideration in river basin management under changing climatic situations.

scholarly journals River flow forecasting by comparative analysis of multiple input and multiple output models form using ANN

2021 ◽  
Author(s):  
S. Agarwal ◽  
P. J. Roy ◽  
P. S. Choudhury ◽  
N. Debbarma
Keyword(s):  
Mass Balance ◽  
River Flow ◽  
Multiple Input Multiple Output ◽  
The United States ◽  
Coefficient Of Correlation ◽  
Concurrent Flow ◽  
Single Output ◽  
Time Flow ◽  
Multiple Input ◽  
Input Multiple Output

Abstract ANN was used to create a storage-based concurrent flow forecasting model. River flow parameters in an unsteady flow must be modeled using a model formulation based on learning storage change variable and instantaneous storage rate change. Multiple input-multiple output (MIMO) and multiple input-single output (MISO models in three variants were used to anticipate flow rates in the Tar River Basin in the United States. Gamma memory neural networks, as well as MLP and TDNNs models, are used in this study. When issuing a forecast, storage variables for river flow must be considered, which is why this study includes them. While considering mass balance flow, the proposed model can provide real-time flow forecasting. Results obtained are validated using various statistical criteria such as RMS error and coefficient of correlation. For the models, a coefficient of correlation value of more than 0.96 indicates good results. While considering the mass balance flow, the results show flow fluctuations corresponding to expressly and implicitly provided storage variations.

scholarly journals Vulnerability of groundwater resources to interaction with river water in a boreal catchment

2015 ◽  
Vol 19 (7) ◽  
pp. 3015-3032 ◽  
Author(s):  
A. Rautio ◽  
A.-L. Kivimäki ◽  
K. Korkka-Niemi ◽  
M. Nygård ◽  
V.-P. Salonen ◽  
...  
Keyword(s):  
Water Intake ◽  
Groundwater Resources ◽  
Groundwater Discharge ◽  
River System ◽  
River Basin Management ◽  
Low Flow ◽  
Main River ◽  
Main River Channel ◽  
Longitudinal Temperature ◽  
Risk Areas

Abstract. A low-altitude aerial infrared (AIR) survey was conducted to identify hydraulic connections between aquifers and rivers and to map spatial surface temperature patterns along boreal rivers. In addition, the stable isotopic compositions (δ18O, δD), dissolved silica (DSi) concentrations and electrical conductivity of water in combination with AIR data were used as tracers to verify the observed groundwater discharge into the river system in a boreal catchment. Based on low temperature anomalies in the AIR survey, around 370 groundwater discharge sites were located along the main river channel and its tributaries (203 km altogether). On the basis of the AIR survey, the longitudinal temperature patterns of the studied rivers differed noticeably. The stable isotopes and DSi composition revealed major differences between the studied rivers. The groundwater discharge locations identified in the proximity of 12 municipal water intake plants during the low-flow seasons should be considered as potential risk areas for water intake plants during flood periods (groundwater quality deterioration due to bank infiltration), and should be taken under consideration in river basin management under changing climatic situations.

Identifying factors leading to hurricane induced landslide dam flood risk in Dominica

2020 ◽  
Author(s):  
Mark Trigg ◽  
Andrew Carr ◽  
Stephanie Trigg
Keyword(s):  
At Risk ◽  
Landslide Dam ◽  
River System ◽  
Flood Pulse ◽  
Landslide Susceptibility Mapping ◽  
Landslide Risk ◽  
Flood Peak ◽  
Main River ◽  
Design Changes ◽  
Landslide Event

&lt;p&gt;Landslide dams occur when the debris from a landslide blocks, fully or partially, a river channel or floodplain. The landslide event often occurs during periods of heavy, intense rainfall, for example during hurricanes and tropical storms. This means that the blocked river is usually at high flow when the dam occurs, resulting in large volumes of water building up behind the dam. Due to the unconsolidated nature of the material blocking the river and large volumes of water behind it, it often does not take long for the dam to fail, releasing an enormous pulse of flood water down the river system. This flood pulse can cause enormous damage and modelling estimates show it can result in a flood peak from a catchment in the order of 3 to 4 times the flood peak that might be expected from the catchment under none-landside conditions. The island of Dominica in the Caribbean has suffered recently from two major catastrophic events, 2015 Tropical Storm Erica and 2017 Hurricane Maria. During these events there were many such landslide dam burst that brought significant damage to infrastructure such as bridges, housing as well as loss of lives.&lt;/p&gt;&lt;p&gt;We report on current research into understanding landslide dam risk on the island, funded by the World Bank as part of efforts to increase resilience of the islands infrastructure to hurricane induced hazards. The island has over one hundred main river systems, all of which are relatively steep due to the volcanic nature of the island and have therefore have significant landslide risk. We are aiming to answer the following questions with our research: (i) Which river catchments are most at risk from these dam-burst events and why; (ii) What evidence is available for landslides that blocked rivers during the last two major events; (iii) What are the scale of these events. We are carrying out geospatial analysis using a combination of landslide susceptibility mapping, river proximity analysis and LiDAR data recently collected for the island as well as landslide inventories for validation.&lt;/p&gt;&lt;p&gt;We will be using the understanding gained from this research to identify catchments most at risk, what infrastructure is exposed to this risk, what mitigation might be effective in reducing the risk, and finally what design changes to the infrastructure could be made to make it more resilient to these hazards.&lt;/p&gt;

scholarly journals Flood forecasting and flood flow modeling in a river system using ANN

2021 ◽  
Author(s):  
S. Agarwal ◽  
P. J. Roy ◽  
P. Choudhury ◽  
N. Debbarma
Keyword(s):  
Network Architecture ◽  
River Flow ◽  
Multiple Input Multiple Output ◽  
River System ◽  
Vital Role ◽  
Statistical Parameters ◽  
Flow Parameters ◽  
Model Form ◽  
Input Multiple Output ◽  
Mimo Model

Abstract In terms of predicting the flow parameters of a river system, such as discharge and flow depth, the continuity equation plays a vital role. In this research, static- and routing-type dynamic artificial neural networks (ANNs) were incorporated in the multiple sections of a river flow on the basis of a storage parameter. Storage characteristics were presented implicitly and explicitly for various sections in a river system satisfying the continuity norm and mass balance flow. Furthermore, the multiple-input multiple-output (MIMO) model form having two base architectures, namely, MIMO-1 and MIMO-2, was accounted for learning fractional storage and actual storage variations and characteristics in a given model form. The model architecture was also obtained by using a trial-and-error approach, while the network architecture was acquired by employing gamma memory along with use of the multi-layer perceptron model form. Moreover, this paper discusses the comparisons and differences between both models. The model performances were validated using various statistical criteria, such as the root-mean-square error (whose value is less than 10% from the observed mean), the coefficient of efficiency (whose value is more than 0.90), and various other statistical parameters. This paper suggests applicability of these models in real-time scenarios while following, continuity norm.

scholarly journals The conservation status of the Fishing Cat Prionailurus viverrinus Bennett, 1833 (Carnivora: Felidae) In Koshi Tappu Wildlife Reserve, Nepal

2016 ◽  
Vol 8 (1) ◽  
pp. 8323 ◽  
Author(s):  
Iain Rothie Taylor ◽  
Hem Sagar Baral ◽  
Prava Pandey ◽  
Prativa Kaspal
Keyword(s):  
Conservation Status ◽  
River System ◽  
Fish Farming ◽  
Buffer Zone ◽  
River Channel ◽  
Main River ◽  
Main River Channel ◽  
Over Exploitation ◽  
Endangered Status ◽  
Wildlife Reserve

<p>The status of the Fishing Cat <em>Prionailurus viverrinus</em> in Koshi Tappu Wildlife Reserve, Nepal was assessed by camera trapping and pugmark searches from 2011 to 2014.  The reserve is a highly dynamic and unstable snow-fed braided river system with many anabranches and islands.  Evidence of Fishing Cats was found throughout most of the reserve.  They were probably more abundant on the eastern side, among the islands of the main river channel, and in the adjacent buffer zone where there was a chain of fishponds and marsh areas fed by seepage from the main river channel.  Evidence of Fishing Cats was found up to 6km north of the reserve on the Koshi River but not beyond this.  The population is probably small and may be isolated but given the endangered status of the species, is significant.  The main likely threats identified are wetland and riparian habitat deterioration caused by over exploitation and illegal grazing by villagers, overfishing of wetlands and rivers within the reserve, and direct persecution arising from perceived conflicts with fish farming and poultry husbandry.  Required conservation actions are discussed.</p><div> </div>

Morphotectonic Analysis of Tanjung Bungo Area Based on Geological Structure Control, Central Sumatera Basin

2020 ◽  
Author(s):  
D., A., L., A. Putri
Keyword(s):  
Natural Resources ◽  
River Flow ◽  
Measurement Data ◽  
River System ◽  
Flow Patterns ◽  
Source Rocks ◽  
Aerial Photographs ◽  
Morphological Data ◽  
Tectonic Activity ◽  
Geological Structures

Tectonic activity in an area could result in various impacts such as changes in elevation, level of slope percentages, river flow patterns and systems, and the formation of geological structures both locally and regionally, which will form a new landscape. The tectonic activity also affects the stratigraphic sequences of the area. Therefore, it is necessary to study morphotectonic or landscape forms that are influenced by active tectonic activities, both those occur recently and in the past. These geological results help provide information of the potential of natural resources in and around Tanjung Bungo area. Morphological data are based on three main aspects including morphogenesis, morphometry, and morphography. The data are collected in two ways, the first is field survey by directly observing and taking field data such as measuring geological structures, rock positions, and outcrop profiles. The second way is to interpret them through Digital Elevation Model (DEM) and aerial photographs by analyzing river flow patterns and lineament analysis. The field measurement data are processed using WinTensor, Dips, and SedLog Software. The supporting data such as Topographic Maps, Morphological Elevation Maps, Slope Maps, Flow Pattern Maps, and Lineament Maps are based on DEM data and are processed using ArcGis Software 10.6.1 and PCI Geomatica. Morphotectonically, the Tanjung Bungo area is at a moderate to high-class level of tectonic activity taken place actively resulted in several joints, faults, and folds. The formation of geological structures has affected the morphological conditions of the area as seen from the development of steep slopes, structural flow patterns such as radial, rectangular, and dendritic, as well as illustrated by rough surface relief in Tanjung Bungo area. This area has the potential for oil and gas resources as indicated by the Telisa Formation, consisting of calcareous silts rich in planktonic and benthonic fossils, which may be source rocks and its contact with the Menggala Formation which is braided river system deposits that could be good reservoirs. Further research needs to be done since current research is only an interpretation of surface data. Current natural resources being exploited in Tanjung Bungo region are coals. The coals have thicknesses of 5-7 cm and are classified as bituminous coals.

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