Extenuating the parameters using HEC-HMS hydrological model for ungauged catchment in the central Omo-Gibe Basin of Ethiopia

Characteristics of ungauged catchments can be studied from the hydrological model parameters of gauged catchments. In this research, discharge prediction was carried out in ungauged catchments using HEC-HMS in the central Omo-Gibe basin. Linear regression, spatial proximity, area ratio, and sub-basin mean were amalgamated for regionalization. The regional model parameters of the gauged catchment and physical characteristics of ungauged catchments were collated together to develop the equations to predict discharge from ungauged catchments. From the sensitivity analysis, crop coefficient (CC), storage coefficient (R), constant rate (CR), and time of concentration (TC) are found to be more sensitive than others. The model efficiency was evaluated using Nash–Sutcliffe Efficiency (N_SE) which was greater than 0.75, varying between ?10% and +10% and the coefficient of determination (R²) was approximated to be 0.8 during the calibration and validation period. The model parameters in ungauged catchments were determined using the regional model (linear regression), sub-basin mean, area ratio, and spatial proximity methods, and the discharge was simulated using the HEC-HMS model. Linear regression was used in the prediction where p-value ≤ 0.1, determination coefficient (R²) = 0.91 for crop coefficient (CC) and 0.99 for maximum deficit (MD). Constant rate (CR), maximum storage (MS), initial storage (IS), storage coefficient (R), and time of concentration (TC) were obtained. The result is that an average of 30 m³/s and 15 m³/s as the maximum monthly simulated flow for ungauged sub-catchments, i.e. Denchiya and Mansa of the main river basin .     

Holistic approach of GIS based Multi-Criteria Decision Analysis (MCDA) and WetSpass models to evaluate groundwater potential in Gelana watershed of Ethiopia

Appropriate quantification and identification of the groundwater distribution in a hydrological basin may provide necessary information for effective management, planning and development of groundwater resources. Groundwater potential assessment and delineation in a highly heterogeneous environment with limited Spatiotemporal data derived from Gelana watershed of Abaya Chamo lake basin is performed, using integrated multi-criteria decision analysis (MCDA), water and energy transfer between soil and plant and atmosphere under quasi-steady state (WetSpass) models. The outputs of the WetSpass model reveal a favorable structure of water balance in the basin studied, mainly using surface runoff. The simulated total flow and groundwater recharge are validated using river measurements and estimated baseflow at two gauging stations located in the study area, which yields a good agreement. The WetSpass model effectively integrates a water balance assessment in a geographical information system (GIS) environment. The WetSpass model is shown to be computationally reputable for such a remote complex setting as the African rift, with a correlation coefficient of 0.99 and 0.99 for total flow and baseflow at a significant level of p-value<0.05, respectively. The simulated annual water budget reveals that 77.22% of annual precipitation loses through evapotranspiration, of which 16.54% is lost via surface runoff while 6.24% is recharged to the groundwater. The calibrated groundwater recharge from the WetSpass model is then considered when determining the controlling factors of groundwater occurrence and formation, together with other multi-thematic layers such as lithology, geomorphology, lineament density and drainage density. The selected five thematic layers through MCDA are incorporated by employing the analytical hierarchy process (AHP) method to identify the relative dominance in groundwater potential zoning. The weighted factors in the AHP are procedurally aggregated, based on weighted linear combinations to provide the groundwater potential index. Based on the potential indexes, the area then is demarcated into low, moderate, and high groundwater potential zones (GWPZ). The identified GWPZs are finally examined using the existing groundwater inventory data (static water level and springs) in the region. About 70.7% of groundwater inventory points are coinciding with the delineated GWPZs. The weighting comparison shows that lithology, geomorphology, and groundwater recharge appear to be the dominant factors influence on the resources potential. The assessment of groundwater potential index values identify 45.88% as high, 39.38% moderate, and 14.73% as low groundwater potential zones. WetSpass model analysis is more preferable in the area like Gelana watershed when the topography is rugged, inaccessible and having limited gauging stations.     

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated by fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. These parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.     

Monitoring litter interception of rainfall using leaf wetness sensor under controlled and field conditions

Leaf litter interception of water is an integral component of the water budget for some vegetated ecosystems. However, loss of rainfall to litter receives considerably less attention than canopy interception due to lack of suitable sensors to measure changes in litter water content. In this study, a commercially available leaf wetness sensor was calibrated to the gravimetric water content of eastern redcedar (Juniperus virginiana ) litter and used to estimate litter interception in a subhumid eastern redcedar woodland in north‐central Oklahoma. Under controlled laboratory conditions, a strong positive correlation between the leaf wetness sensor output voltage (mV) and measured gravimetric litter water content (? _g) was determined: ? _g = (.0009 × mV²) ? (0.14 × mV) ? 11.41 (R ² = .94, p  < .0001). This relationship was validated with field sampling and the output voltage (mV) accounted for 48% of the observed variance in the measured water content. The maximum and minimum interception storage capacity ranged between 1.16 and 12.04 and 1.12 and 9.62 mm, respectively. The maximum and minimum amount of intercepted rain was positively correlated to rainfall amount and intensity. The continuous field measurements demonstrated that eastern redcedar litter intercepted approximately 8% of the gross rainfall that fell between December 16, 2014 and May 31, 2015. Therefore, rainfall loss to litter can constitute a substantial component of the annual water budget. Long‐term in situ measurement of litter interception loss is necessary to gain a better estimate of water availability for streamflow and recharge. This is critical to manage water resources in the south‐central Great Plains, USA where grasslands are rapidly being transformed to woodland or woody dominated savanna.     

Snow cover depletion under changed climate with the help of remote sensing and temperature data

Snow cover depletion curve (SDC) is one of the important variables in snow hydrological applications, and these curves are very much required for snowmelt runoff modeling in a snowfed catchment. Remote sensing is an important source of snow cover area which is used for preparation of SDC. Snow cover maps produced by Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are one of the best source of satellite-based snow cover area at a regular interval. Therefore, in this study, snow cover maps have been prepared for the years 2000?C2005 using MODIS data. The study area chosen viz. Beas basin up to Pandoh dam falls in western Himalayan region. For snowmelt runoff modeling, catchment is divided into number of elevation zones and SDC is required for each zone. When sufficient satellite data are not available due to cloud cover or due to some other reasons, then SDC can to be generated using temperature data. Under changed climate conditions also, modified SDC is required. Therefore, to have SDC under such situations, a relationship between snow cover area and cumulative mean temperature has been developed for each zone of the catchment. This procedure of having snow cover maps has two main purposes. First, it could potentially be used to generate snow cover maps when cloud-free satellite data are not available. Second, it can be used to generate snow-covered area in a new climate to see the impact of climate change on snowmelt runoff studies.     

Computing the 3D in-situ stress field from shut-in pressure data using statistical regression

The paper describes a multivariable statistical regression technique for computing the 3D stress tensor applied to the shut-in pressure data obtained on fractures during in-situ stress measurement by hydraulic fracturing in a short borehole. This method computes the mean value of components of the 3D stress tensor and their confidence intervals at a desired confidence level. This has been applied to the data of shut-in pressure from Narwapahar mine, India and Kamaishi mine, Japan. The computed in-situ stress tensor is corroborated with that obtained by other methods.     

Habitat range of two alpine medicinal plants in a trans-Himalayan dry valley, Central Nepal

Understanding of the habitat range of threatened Himalayan medicinal plants which are declining in their abundance due to high anthropogenic disturbances is essential for developing conservation strategies and agrotechnologies for cultivation. In this communication, we have discussed the habitat range of two alpine medicinal plants, Aconitum naviculare （Bruehl） Stapf and Neopicrorhiza scrophulariiflora （Pennel） Hong in a trans-Himalayan dry valley of central Nepal, Manang district. They are the most prioritized medicinal plants of the study area in terms of ethnomedicinal uses. A. naviculare occurs on warm and dry south facing slopes between 4090-4650 m asl along with sclerophyllous and thorny alpine scrubs, while N. scrophulariiflora is exclusively found on cool and moist north facing slope between 4000 and 4400 m asl where adequate water is available from snow melt to create a suitable habitat for this wetland dependent species. The soil in rooting zone of the two plants differs significantly in organic carbon （OC）, organic matter （OM）, total nitrogen （N） and carbon to nitrogen （C/N） ratio. Due to cool and moist condition of N. scrophulariiflora habitat, accumulation of soil OC is higher, but soil N content is lower probably due to slow release from litter, higher leaching loss and greater retention in perennial live biomass of the plant. The C/N ratio of soil is more suitable in A. navuculare habitat than that of N scrophulariiflora for N supply. Warm and sunny site with N rich soil can be suitable for cultivation ofA. naviculare, while moist and cool site with organic soil for N. scrophulariiflora. The populations of both the plants are fragmented and small. Due to collection by human and trampling damage by livestock, the population of A. naviculare was found absent in open areas in five of the six sampling sites and it was confined only within the bushes of alpine scrubs. For N. serophulariiflora, high probability of complete receding of small glaeiers may be a new threat in future to its habitat. The information about habitat conditions, together with the information from other areas, ean be useful to identify potential habitats and plan for cultivation or domestication of the two medieinal plants.     

GCP collection for corona satellite photographs: Issues and methodology

Use of high-resolution and historic CORONA satellite photographs for mapping and other purposes requires Ground Control Points (GCPs), as ephemeris data and image parameters are not available. However, the alterations in landscape in last 34 years (i.e., since the acquisition of these photographs) prevent identification and collection of large number of GCPs in the field. This paper presents a methodology for collection of GCPs for CORONA photographs. The advantages and limitations of the methodology are discussed. For a study site, situated in Siwaliks and Lower Himalayas, the GCPs were identified in CORONA photographs and their WGS84 coordinates were estimated through a process of datum transformation and georeferencing. Estimated GCP coordinates from the topo sheets and 2D and 3D views of photographs, helped in identifying the GCP locations in field, which were observed using DGPS. Investigations were carried out to relate Differential Global Positioning System (DGPS) accuracy with base line length and time of observation. Abase line of 350 km and half an hour observation were found appropriate to yield accuracy in GCP collection by DGPS method, which conforms to CORONA resolution of 3 m.     

Comparative study of neural network,fuzzy logic and linear transfer function techniques in daily rainfall‐runoff modelling under different input domains

This paper compares artificial neural network (ANN), fuzzy logic (FL) and linear transfer function (LTF)‐based approaches for daily rainfall‐runoff modelling. This study also investigates the potential of Takagi‐Sugeno (TS) fuzzy model and the impact of antecedent soil moisture conditions in the performance of the daily rainfall‐runoff models. Eleven different input vectors under four classes, i.e. (i) rainfall, (ii) rainfall and antecedent moisture content, (iii) rainfall and runoff and (iv) rainfall, runoff and antecedent moisture content are considered for examining the effects of input data vector on rainfall‐runoff modelling. Using the rainfall‐runoff data of the upper Narmada basin, Central India, a suitable modelling technique with appropriate model input structure is suggested on the basis of various model performance indices. The results show that the fuzzy modelling approach is uniformly outperforming the LTF and also always superior to the ANN‐based models. Copyright © 2010 John Wiley & Sons, Ltd.     

Human-Wildlife Conflicts in Paschim Kusaha Village of Koshi Tappu Wildlife Reserve,Sunsari District,Nepal

Human-wildlife conflict has been one of the most trouble-causing issues in many areas of Nepal including Eastern Nepal. This study assessed the human-wildlife conflict status in Paschim Kusaha Village of Koshi Tappu Wildlife Reserve (KTWR), Sunsari District, Nepal. Data were collected from 47 respondents of different households through questionnaire surveys and formal and informal interviews. Results revealed that the most destructive wild animals were wild elephants, wild boar, and wild water buffalo and the most raided crops were paddy (63.83 %), maize (19.15%), and potato (17.02%). Most of the encounters between humans and wildlife were recorded at night (after dusk and before dawn) (78.72%). Local people were suffering from damage of physical properties, human harassment or nuisance, and depredation of cropland due to wild animals. A total of 70% of respondents had a positive attitude towards conservation despite disturbing human mortality records (22 deaths in the last five years) from the reserve area and surrounding. Awareness of wildlife behavior together with conservation and easy access to compensation schemes were suggested to minimize conflicts in the area.