Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Detection of moisture stress by indicator plots — A simulation

The possibility of advanced indication of moisture stress in a crop by small prepared plots with compacted or partially sand-substituted soils is examined by an analytical simulation. A series of soils and three crops are considered for the simulation. The moisture characteristics of the soils are calculated with an available model. Using average potential evapotranspiration values and a simple actual evapotranspiration model, the onset of moisture stress in the natural and indicator plots is calculated for different degrees of sand substitution and compaction. Cases where sand substitution fails are determined. The effect of intervening rainfall and limited root depth on the beginning of moisture stress is investigated.

Ecology of the swampy relic forests of Kathalekan from central Western Ghats, India

Introduction of agriculture three millennia ago in Peninsular India’s Western Ghats altered substantially ancient tropical forests. Early agricultural communities, nevertheless, strived to attain symbiotic harmony with nature as evident from prevalence of numerous sacred groves, patches of primeval forests sheltering biodiversity and hydrology. Groves enhanced heterogeneity of landscapes involving elements of successional forests and savannas favouring rich wildlife. A 2.25 km2 area of relic forest was studied at Kathalekan in Central Western Ghats. Interspersed with streams studded with Myristica swamps and blended sparingly with shifting cultivation fallows, Kathalekan is a prominent northernmost relic of southern Western Ghat vegetation. Trees like Syzygium travancoricum (Critically Endangered), Myristica magnifica (Endangered) and Gymnacranthera canarica (Vulnerable) and recently reported Semecarpus kathalekanensis, are exclusive to stream/swamp forest (SSF). SSF and non-stream/swamp forest (NSSF) were studied using 18 transects covering 3.6 ha. Dipterocarpaceae, its members seldom transgressing tropical rain forests, dominate SSF (21% of trees) and NSSF (27%). The ancient Myristicaceae ranks high in tree population (19% in SSF and 8% in NSSF). Shannon-Weiner diversity for trees is higher (>3) in six NSSF transects compared to SSF (<3). Higher tree endemism (45%), total endemic tree population (71%) and significantly higher above ground biomass (349 t/ha) cum carbon sequestration potential (131 t/ha) characterizes SSF. Faunal richness is evident from amphibians (35 species - 26 endemics, 11 in IUCN Red List). This study emphasizes the need for bringing to light more of relic forests for their biodiversity, carbon sequestration and hydrology. The lives of marginal farmers and forest tribes can be uplifted through partnership in carbon credits, by involving them in mitigating global climatic change through conservation and restoration of high biomass watershed forests.

Response of fungal and actinobacterial communities to water-level drawdown in boreal peatland sites

"We used PCR-DGGE fingerprinting and direct sequencing to analyse the response of fungal and actinobacterial communities to changing hydrological conditions at 3 different sites in a boreal peatland complex in Finland. The experimental design involved a short-term (3 years; STD) and a long-term (43 years; LTD) water-level drawdown. Correspondence analyses of DGGE bands revealed differences in the communities between natural sites representing the nutrient-rich mesotrophic fen, the nutrient-poorer oligotrophic fen, and the nutrient-poor ombrotrophic bog. Still, most fungi and actinobacteria found in the pristine peatland seemed robust to the environmental variables. Both fungal and actinobacterial diversity was higher in the fens than in the bog. Fungal diversity increased significantly after STD whereas actinobacterial diversity did not respond to hydrology. Both fungal and actinobacterial communities became more similar between peatland types after LTD, which was not apparent after STD. Most sequences clustered equally between the two main fungal phyla Ascomycota and Basidiomycota. Sequencing revealed that basidiomycetes may respond more (either positively or negatively) to hydrological changes than ascomycetes. Overall, our results suggest that fungal responses to water-level drawdown depend on peatland type. Actinobacteria seem to be less sensitive to hydrological changes, although the response of some may similarly depend on peatland type. (C) 2009 Elsevier Ltd. All rights reserved."

Estimation of variables at ungaged locations by empirical orthogonal functions

A technique based on empirical orthogonal functions is used to estimate hydrologic time-series variables at ungaged locations. The technique is applied to estimate daily and monthly rainfall, temperature and runoff values. The accuracy of the method is tested by application to locations where data are available. The second-order characteristics of the estimated data are compared with those of the observed data. The results indicate that the method is quick and accurate.

Analysis of an Aquifer-water table aquitard system

The problem of pumping an aquifer in an aquifer-water table aquitard system is considered, accounting for the elastic properties of both the aquifer and the aquitard, the gravity drainage in the aquitard and treating the water table as an unknown boundary. The coupled partial differential equations are nondimensionalised, yielding three principal parameters governing the problem. The numerical solution of these equations is obtained for a wide range of parameter values. Type curves are generated and their use is illustrated through a field application.

Analysis of flow near a dug well in an unconfined aquifer

A numerical analysis of flow to a dug well in an unconfined aquifer is made, taking into account well storage, elastic storage release, gravity drainage, anisotropy, partial penetration, vertical flow and seepage surface at the well face, and treating the water table in the aquifer and water level in the well as unknown boundaries. The pumped discharge is maintained constant. The solution is obtained by a two-level iterative scheme. The effects of governing parameters on the drawdown, development of seepage surface and contribution from aquifer flow to the total discharge are discussed. The degree of anisotropy and partial penetration are found to be the parameters which affect the flow characteristics most significantly. The effect of anisotropy on the development of seepage surface is very pronounced.

Meridional propagation of large-scale monsoon convective zones

Observational studies indicate that the convective activity of the monsoon systems undergo intraseasonal variations with multi-week time scales. The zone of maximum monsoon convection exhibits substantial transient behavior with successive propagating from the North Indian Ocean to the heated continent. Over South Asia the zone achieves its maximum intensity. These propagations may extend over 3000 km in latitude and perhaps twice the distance in longitude and remain as coherent entities for periods greater than 2-3 weeks. Attempts to explain this phenomena using simple ocean-atmosphere models of the monsoon system had concluded that the interactive ground hydrology so modifies the total heating of the atmosphere that a steady state solution is not possible, thus promoting lateral propagation. That is, the ground hydrology forces the total heating of the atmosphere and the vertical velocity to be slightly out of phase, causing a migration of the convection towards the region of maximum heating. Whereas the lateral scale of the variations produced by the Webster (1983) model were essentially correct, they occurred at twice the frequency of the observed events and were formed near the coastal margin, rather than over the ocean. Webster's (1983) model used to pose the theories was deficient in a number of aspects. Particularly, both the ground moisture content and the thermal inertia of the model were severely underestimated. At the same time, the sea surface temperatures produced by the model between the equator and the model's land-sea boundary were far too cool. Both the atmosphere and the ocean model were modified to include a better hydrological cycle and ocean structure. The convective events produced by the modified model possessed the observed frequency and were generated well south of the coastline. The improved simulation of monsoon variability allowed the hydrological cycle feedback to be generalized. It was found that monsoon variability was constrained to lie within the bounds of a positive gradient of a convective intensity potential (I). The function depends primarily on the surface temperature, the availability of moisture and the stability of the lower atmosphere which varies very slowly on the time scale of months. The oscillations of the monsoon perturb the mean convective intensity potential causing local enhancements of the gradient. These perturbations are caused by the hydrological feedbacks, discussed above, or by the modification of the air-sea fluxes caused by variations of the low level wind during convective events. The final result is the slow northward propagation of convection within an even slower convective regime. The ECMWF analyses show very similar behavior of the convective intensity potential. Although it is considered premature to use the model to conduct simulations of the African monsoon system, the ECMWF analysis indicates similar behavior in the convective intensity potential suggesting, at least, that the same processes control the low frequency structure of the African monsoon. The implications of the hypotheses on numerical weather prediction of monsoon phenomenon are discussed.

Kaupunkipurot Helsingissä - Veden laatu vuonna 2004

In recent years urban hydrology and individual urban streams have been in focus and subjects to research also in Helsinki. However, until now there has been lack of research covering simultaneously the whole area of the city of Helsinki. The aim of this study was to find out the general state of water quality in small urban streams in the city of Helsinki. 21 streams were studied: Mätäjoki, Korppaanoja, Mätäpuro, Näsinoja-Tuomarinkylänoja, Tuomarinkartanonpuro, Kumpulanpuro, Tapaninkylänpuro, Tapaninvainionpuro, Puistolanpuro, Longinoja, Säynäslahdenpuro, Viikinoja, Porolahdenpuro, Mustapuro, Marjaniemenpuro, Mellunkylänpuro, Vuosaarenpuro, Rastilanpuro, Ramsinkannaksenpuro, Skatanpuro and Yliskylänpuro. Water samples were collected from 48 sampling points, each stream having at least one point. Four water samples were collected from each point, sampling periods being 9.-11.2., 26.-28.4., 29.6.-1.7. and 25.-27.10.2004. Field measurements associated with water sampling included water temperature, oxygen concentration, pH and electrical conductivity. Water samples were analysed in the Laboratory of Physical Geography in the University of Helsinki and in the Environmental Laboratory of the City of Helsinki Environment Centre for following properties: suspended solids, dissolved substances, alkalinity, principal anions and cations (Na+, K+, Mg2+, Ca2+, F-, Cl-, NO3-, PO43- and SO42-), colour, turbidity, biological and chemical oxygen demand (BOD7 and CODMn-values), nutrient concentrations and bacterial indicators of hygienic quality. The main water quality issues found in this study were low oxygen levels in many streams and poor hygienic quality at least occasionally. E.g. in summer oxygen levels were under 60 % in every stream. Amount of total dissolved substances and nutrients were high in some of the streams studied. Compared to other Finnish streams the values of alkalinity and pH were higher. Although these problems were common, the variation between different streams and sampling points was significant. This was probably due to local conditions. Best overall water quality was found in Mätäpuro and Tuomarinkartanonpuro streams. Seasonal variation was evident in almost all water quality properties. For example the total amount of dissolved substances was largest in winter and decreased during the year. Colour and turbidity were smallest in winter and increased towards the end of the year. The same was true for suspended solids, which had smallest concentration in winter and greatest in autumn. It must be kept in mind that the spring samples were collected after the spring flood otherwise the largest suspended solid concentrations would have been expected in spring. Finnish general water quality classification was used to assess the quality of urban stream waters. Its suitability for small urban streams is not, however, completely trouble-free. This classification does not take into account the quick changes in such small streams but evaluates only the yearly mean values. This can oversimplify the picture of the water quality situation in the streams. Also in order to better reflect the urban environment the analysed water quality properties should also include total dissolved substances and e.g. concentrations of chloride and sodium.

Field evaluation of unsaturated hydraulic conductivity models and parameter estimation from retention data

Predictions of two popular closed-form models for unsaturated hydraulic conductivity (K) are compared with in situ measurements made in a sandy loam field soil. Whereas the Van Genuchten model estimates were very close to field measured values, the Brooks-Corey model predictions were higher by about one order of magnitude in the wetter range. Estimation of parameters of the Van Genuchten soil moisture characteristic (SMC) equation, however, involves the use of non-linear regression techniques. The Brooks-Corey SMC equation has the advantage of being amenable to application of linear regression techniques for estimation of its parameters from retention data. A conversion technique, whereby known Brooks-Corey model parameters may be converted into Van Genuchten model parameters, is formulated. The proposed conversion algorithm may be used to obtain the parameters of the preferred Van Genuchten model from in situ retention data, without the use of non-linear regression techniques.

Comparison of electrical resistivity by geophysical method and neutron probe logging for soil moisture monitoring in a forested watershed

Geophysical methods are becoming more popular nowadays in the field of hydrology due to their time and space efficiency. So an attempt has been made here to relate electrical resistivity with soil moisture content in the field. The experiments were carried out in an experimental watershed `Mulehole' in southern India, which is a forested watershed with approximately 80% red soil. Five auger holes were drilled to perform the soil moisture and electrical resistivity measurements in a toposequence having red and black soils, with sandy weathered soil at the bottom. Soil moisture was measured using neutron probe and electrical resistivity was measured using electrical logging tool. The results indicate that electrical resistivity measurements can be used to measure soil moisture content for red soils only.

Predictive uncertainty of chaotic daily streamflow using ensemble wavelet networks approach

Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Spatial Variation of Physico-Chemical and hydrological Parameters with land-use in Venkatapura Catchment,Karnataka

Social, economic and political development of a region is dependent on the health and quantity of the natural resources. Integrated approaches in the management of natural resources would ensure sustainability, which demands inventorying, mapping and monitoring of resources considering all components of an ecosystem. The monitoring of hydrological and catchment landscape of river resources have a vital role in the conservation and management of aquatic resources. This paper presents a case study Venkatapura river basin in Uttara Kannada district of Karnataka State, India based on stream hydrology and landuse analyses. The results revealed variations in dissolved oxygen and free carbon dioxide according to the flow nature of the water, and increased amount of phosphates and coliform contamination in streams closer to anthropogenic activities.