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The Palar River basin is one of the major rivers in southern peninsular India. Morphometric analysis coupled with drainage network analysis was carried out for the Palar River basin to understand its drainage characteristics and the drainage network geometry with reference to tectonics. The morphometric analysis has been carried out using 'bearing azimuth and drainage (bAd) calculator' which a new and easy methodology for extraction of watershed morphometric parameters. The entire Palar River basin has been divided into five major sub-basins and various linear, areal, and relief morphometric parameters were calculated. The sub-basins I, II, and III reflect low to medium stream frequency (Fs) and moderate drainage density (Dd) and a high bifurcation ratio of various stream orders signifies that they are surging through tectonically active areas, followed by high overland flow and less recharge into the subsurface resulting in low groundwater potential. Moreover, sub-basins IV and V show the relatively low overland flow, which helps to percolate water, hence ground water potential will be higher. The morphometric result suggests that the drainage network geometry is variously controlled by recent tectonics. Lineaments trending majorly NW-SE, NE-SW, and E-W mark the major drainage network in Palar River drainage basin. Lower order streams and higher order streams follow NW-SE, NE-SW lineaments. Which also points toward the tectonic control of drainage in Palar River. As a result of channel orientation due to tectonic activity: (i) most channels are A-type or B-type associated with the lineaments, (ii) the pattern of the drainage network is dendritic, rectangular sometime trellis too, and (iii) the main rivers flow longitudinally to the predominant lineament direction.

Numerical simulation of mixed flows combining free surface and pressurized flows is a practical tool to prevent possible flood situations in urban environments. When dealing with intense storm events, the limited capacity of the drainage network conduits can cause undesirable flooding situations. Computational simulation of the involved processes can lead to better management of the drainage network of urban areas. In particular, it is interesting to simultaneuously calculate the possible pressurization of the pipe network and the surface water dynamics in case of overflow. In this work, the coupling of two models is presented. The surface flow model is based on two-dimensional shallow water equations with which it is possible to solve the overland water dynamics as well as the transformation of rainfall into runoff through different submodels of infiltration. The underground drainage system assumes mostly free surface flow that can be pressurized in specific situations. The pipe network is modeled by means of one-dimensional sections coupled with the surface model in specific regions of the domain, such as drains or sewers. The numerical techniques considered for the resolution of both mathematical models are based on finite volume schemes with a first-order upwind discretization. The coupling of the models is verified using laboratory experimental data. Furthermore, the potential usefulness of the approach is demonstrated using real flooding data in a urban environment.

The main objective of our studies undertaken is to determine the causes of the increased degradation of the soil from upper terraces of Moldova's river catchment. In the studied area from the western part of the Suceava Plateau (North-Eastern Romania) was built in 1978-1980 with a drainage network consisting of channels and underground drains. These works have been associated with leveling, deep loosening, mole drainage and liming. The studied settlement is located on the terrace platform with an average altitude of 390 m, a relatively flat land (slope 2-5%o). The average values of the climatic parameters have 8.2°C temperature and annual rainfall of 625 mm. The distribution of precipitations in months and seasons are uneven and periodically records a large amounts of rainfall in 24 hours and 1-5 consecutive days. The dominant soils are Glosic, stagnic albic Livisols with poor internal drainage, especially on the illuvial horizon with a clay content of more than 40%. The land use was land in crop but after 1990 it is used as a meadow. Our studies on the characteristics of meadows lands began in 1994 and consisted in the measurement of the absorption drain flows, the determination of the soil humidity and the geometric and hydraulic parameters of the drainage network, state of compactness and bulk density values. Following the studies, it was found that during the period 2008-2018 the degradation of the lands and the drainage-drainage network increased. Land degradation consisted in increasing the surface with water stagnation (i), especially in spring during snow melt, after the summer torrential rains and autumn rainfall. Soil degradation has increased due to the compaction processes (ii) favored by overgrazing (iii), especially when the soil is too wet or poorly covered with vegetation. The enlargement of the surfaces land with water stagnation were due to the clogging of drainage channels and drains (iv), as well as to the micro depressions (v) resulting from the more pronounced local compaction of the soil. Changing the composition of the vegetal cover led to the decrease of grassland quality and to increase susceptibility of the soil degradation.

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP – Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM – the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.

The morphometric characteristics of the Kalvārī basin were analyzed to prioritize sub-basins based on their susceptibility to erosion by water using a remote sensing-based data and a GIS. The morphometric parameters (MPs)—linear, relief, and shape—of the drainage network were calculated using data from the Advanced Land-observing Satellite (ALOS) phased-array L-type synthetic-aperture radar (PALSAR) digital elevation model (DEM) with a spatial resolution of 12.5 m. Interferometric synthetic aperture radar (InSAR) was used to generate the DEM. These parameters revealed the network’s texture, morpho-tectonics, geometry, and relief characteristics. A complex proportional assessment of alternatives (COPRAS)-analytical hierarchy process (AHP) novel-ensemble multiple-criteria decision-making (MCDM) model was used to rank sub-basins and to identify the major MPs that significantly influence erosion landforms of the Kalvārī drainage basin. The results show that in evolutionary terms this is a youthful landscape. Rejuvenation has influenced the erosional development of the basin, but lithology and relief, structure, and tectonics have determined the drainage patterns of the catchment. Results of the AHP model indicate that slope and drainage density influence erosion in the study area. The COPRAS-AHP ensemble model results reveal that sub-basin 1 is the most susceptible to soil erosion (SE) and that sub-basin 5 is least susceptible. The ensemble model was compared to the two individual models using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). To evaluate the prediction accuracy of the ensemble model, its results were compared to results generated by the modified Pacific Southwest Inter-Agency Committee (MPSIAC) model in each sub-basin. Based on SCCT and KTCCT, the ensemble model was better at ranking sub-basins than the MPSIAC model, which indicated that sub-basins 1 and 4, with mean sediment yields of 943.7 and 456.3 m 3 km − 2   year − 1 , respectively, have the highest and lowest SE susceptibility in the study area. The sensitivity analysis revealed that the most sensitive parameters of the MPSIAC model are slope (R2 = 0.96), followed by runoff (R2 = 0.95). The MPSIAC shows that the ensemble model has a high prediction accuracy. The method tested here has been shown to be an effective tool to improve sustainable soil management.

This main objective of this study is flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan. In the study region, flash flood is one of the horrific and recurrent hydro-meteorological disasters causing damages to human life, their properties, and infrastructure. Watershed modeling approach is implemented to delineate Panjkora Basin, its sub-basins, and extract drainage network by utilizing Advance Space borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model as an input data in geographic information system environment. A total of 30 sub-basins were delineated using threshold of 25 km2. The geo-morphometric parameters of each sub-basin were computed by applying Hortonian, Schumm, and Strahler Geo-morphological laws. The value of each parameter was normalized and aggregated into geo-morphometric ranking number depicting the degree of flash flood susceptibility. Surface run-off depth of each sub-basin is estimated by applying Natural Resource Conservation Service Curve Number hydrological model. Both models outputs were integrated by implementing weighted overlay analysis technique and susceptibility map is obtained. The resultant map was analyzed and zonated into very high, high, moderate, low, and very low flash flood susceptibility zones. These zones were spread over an area of 1441 km2 (27%), 1950 km2 (36.5%), 1252 km2 (23.4%), 604 km2 (11.3%), and 98 km2 (1.8%), respectively. Spatially, the very high susceptible zone is located in the upstream areas, characterized by snow covered peaks, steep gradient (> 30°), and high drainage density (> 1.7 km/km2), and geologically dominated by igneous and metamorphic lithological units. Analysis indicated that flash flood susceptibility is directly increases with increasing surface run-off and geo-morphometric ranking number. A new model is developed to geo-visualize the spatial pattern of flash flood susceptibility. Accuracy of the model is assessed using global positioning system-based primary data regarding past-flood damages and flood marks. The study results can facilitate Disaster Management Authorities and flood dealing line agencies to initiate location-specific flood-risk reduction strategies in highly susceptible areas of Panjkora Basin. Similarly, this methodological approach can be adapted for any highland river system.

The quality of water in many urban rivers in Latin America is increasingly degrading due to wastewater and runoff discharges from urban sprawl. Due to deficits in sanitary drainage systems, greywater is discharged to the stormwater drainage network generating a continuous dryweather runoff that reaches rivers without treatment. One of the main challenges in the region is to achieve sustainable management of urban runoff for the recovery of rivers ecosystem integrity. However, retrofitting conventional centralized wastewater drainage networks into the existing urban grid represents important social, economic and technical challenges. This paper presents an alternative adaptive methodology for the design of Naturebased Solutions for decentralized urban runoff treatment. Through this study, technical solutions commonly used for stormwater management were adapted for dry-weather runoff treatment and co-designed for the particular conditions of a representative study area, considering space availability as the main constraining factor for retrofitting in urban areas. The application of a co-design process in a dense neighbourhood of the Great Metropolitan area of Costa Rica brought to light valuable insights about conditions that could be hindering the implementation of NBS infrastructures in Latin America.

The main purpose of this study is to compare the performance of two statistical analysis models like weight of evidence and logistic regression (LR) with a soft computing model like artificial neural networks for landslide susceptibility assessment. These models were applied for the Selinous River drainage basin (northern Peloponnese, Greece) in order to map landslide susceptibility and rate the importance of landslide causal factors. A landslide inventory was prepared using satellite imagery interpretation and field surveys. Eight causal factors including altitude, slope angle, slope aspect, distance to road network, distance to drainage network, distance to tectonic elements, land cover, and lithology were considered. Model performance was tested with receiver operator characteristic analysis. The validation findings revealed that the three models show promising results since they give good accuracy values. However, the LR model proved to be relatively superior in estimating landslide susceptibility throughout the study area.

Morphometric parameters can be useful tools to provide general understanding of physical characteristics of drainage basin with respect to floods. To evaluate the flood influencing factors in the upper Jhelum basin, we delineate the upper Jhelum basin into ten sub-basins, followed by extraction of drainage network and morphometric parameters using Advanced Spaceborne Thermal Emission and Reflection Radiometer digital elevation model and topographic maps in Geographic Information System. The overall flood potential was determined on the basis of compound value obtained for all morphometric parameters of each sub-basin. The analysis reveals that, in general, the northeastern segment of the upper Jhelum basin reveals comparative higher flood potential than the southwestern segment. The tributaries, such as Lidder, Veshav, Arapal, Arapat, and Bring, exhibit greater potential to produce peak flows during rainfall events, while the tributaries like Dudhganga, Rambiara, Sandran, Romushi, and Sasara express moderate-to-low flood potential, respectively. The results of this study are likely to be very useful for effective flood hazard mitigation in upper Jhelum floodplain.

Dendritic, i.e., tree-like, river networks are ubiquitous features on Earth’s landscapes; however, how and why river networks organize themselves into this form are incompletely understood. A branching pattern has been argued to be an optimal state. Therefore, we should expect models of river evolution to drastically reorganize (suboptimal) purely nondendritic networks into (more optimal) dendritic networks. To date, current physically based models of river basin evolution are incapable of achieving this result without substantial allogenic forcing. Here, we present a model that does indeed accomplish massive drainage reorganization. The key feature in our model is basin-wide lateral incision of bedrock channels. The addition of this submodel allows for channels to laterally migrate, which generates river capture events and drainage migration. An important factor in the model that dictates the rate and frequency of drainage network reorganization is the ratio of two parameters, the lateral and vertical rock erodibility constants. In addition, our model is unique from others because its simulations approach a dynamic steady state. At a dynamic steady state, drainage networks persistently reorganize instead of approaching a stable configuration. Our model results suggest that lateral bedrock incision processes can drive major drainage reorganization and explain apparent long-lived transience in landscapes on Earth.