Catchment In India Research Articles

Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs

This work evaluates the impact of climate change on the water balance of a catchment in India. Rainfall and hydro-meteorological variables for current (20C3M scenario, 1981–2000) and two future time periods: mid of the 21st century (2046–2065) and end of the century (2081–2100) are simulated using Modified Markov Model-Kernel Density Estimation (MMM-KDE) and k-nearest neighbor downscaling models. Climate projections from an ensemble of 5 GCMs (MPI-ECHAM5, BCCR-BCM2.0, CSIRO-mk3.5, IPSL-CM4, and MRI-CGCM2) are used in this study. Hydrologic simulations for the current as well as future climate scenarios are carried out using Soil and Water Assessment Tool (SWAT) integrated with ArcGIS (ArcSWAT v.2009). The results show marginal reduction in runoff ratio, annual streamflow and groundwater recharge towards the end of the century. Increased temperature and evapotranspiration project an increase in the irrigation demand towards the end of the century. Rainfall projections for the future shows marginal increase in the annual average rainfall. Short and moderate wet spells are projected to decrease, whereas short and moderate dry spells are projected to increase in the future. Projected reduction in streamflow and groundwater recharge along with the increase in irrigation demand is likely to aggravate the water stress in the region under the future scenario.

Importance of spatially distributed hydrologic variables for land use change modeling

Land use changes have a pronounced impact on hydrology. Vice versa, hydrologic changes affect land use patterns. The objective of this study is to test whether hydrologic variables can explain land use change. We employ a set of spatially distributed hydrologic variables and compare it against a set of commonly used explanatory variables for land use change. The explanatory power of these variables is assessed by using a logistic regression approach to model the spatial distribution of land use changes in a meso-scale Indian catchment. When hydrologic variables are additionally included, the accuracies of the logistic regression models improve, which is indicated by a change in the relative operating characteristic statistic (ROC) by up to 11%. This is mostly due to the complementarity of the two datasets that is reflected in the use of 44% commonly used variables and 56% hydrologic variables in the best models for land use change.

Regional flood frequency analysis: comparison of L-moment and conventional approaches for an Indian catchment

A realistic estimation of flood magnitude for a given return period is essential for successful operation and economical design of pivotal hydraulic structures such as dams, reservoirs and spillways, bridges, small culverts, urban drainage systems, flood plain zoning, economic evaluation of flood protection projects, etc. The flood frequency analysis is generally used for flood estimation, entirely based on the assumption that the floods are random and the floods in future are supposed to bear similar statistical properties that have occurred in the past. If adequate data are available at-site flood frequency analysis is used, otherwise regional flood frequency analysis (RFFA) is preferred for flood estimation. The RFFA for various small and medium catchments of India with different approaches have been carried out and reported in the literature. The focus of the present study is to carry out the RFFA using different approaches i.e. conventional method and L-moment and comparing the results for the Krishna and Penner subzone 3(h) of India. It was found that the values of growth factors obtained by the conventional method are higher than those of L-moment methods, thus leading to conservative estimate of the peak floods.

Response of streamflow to projected climate change scenarios in an eastern Himalayan catchment of India

Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios for an eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of Arunachal Pradesh with an area of 52 km2 is selected for the present study with an elevation range of 3143–4946 m above mean sea level. Satellite images from October to June of the selected hydrological year 2006–2007 were procured from National Remote Sensing Centre, Hyderabad. Snow cover mapping is done using NDSI method. Based on long term meteorological data, temperature and precipitation data of selected hydrological year are normalized to represent present climatic condition. The projected temperature and precipitation data are downloaded from NCAR’s GIS data portal for different emission scenarios (SRES), viz., A1B, A2, B1; and IPCC commitment (non-SRES) scenario for different future years (2020, 2030, 2040 and 2050). Projected temperature and precipitation data are obtained at desired location by spatially interpolating the gridded data and then by statistical downscaling using linear regression. Snow depletion curves for all projected scenarios are generated for the study area and compared with conventional depletion curve for present climatic condition. Changes in cumulative snowmelt depth for different future years are highest under A1B and lowest under IPCC commitment, whereas A2 and B1 values are in-between A1B and IPCC commitment. Percentage increase in streamflow for different future years follows almost the same trend as change in precipitation from present climate under all projected climatic scenarios. Hence, it was concluded that for small catchments having seasonal snow cover, the total streamflow under projected climatic scenarios in future years will be primarily governed by the change in precipitation and not by change in snowmelt depth. Advancing of depletion curves for different future years are highest under A1B and lowest under IPCC commitment. A2 and B1 values are in-between A1B and IPCC commitment.

Consequences of Continuous Zero Values and Constant Values in Time Series Modeling: Understanding through Chaotic Approach

AbstractThis study is aimed at understanding the behavior of a rainfall time series having a large number of continuous zero values. Forty-nine years of daily rainfall data pertaining to the Koyna Reservoir catchment in India is employed in the study. The majority of rainfall happens during the monsoon period from June to September; the rainfall during the non-monsoon period (October to May) is almost negligible. This phenomenon has been observed every year. Hence, 64% of the time series contains zero values. Six sets of rainfall time series along with the observed series are analyzed: (1) daily observed average rainfall data; (2) daily transformed average rainfall data; (3) daily wet-period average rainfall data; (4) phase-randomized average rainfall data; (5) daily average rainfall anomaly data; and (6) standardized daily average rainfall anomaly data. To understand the consequence of a greater length of zero values and constant values, daily observed average rainfall data results are compared with dail...

Determination of Effective Impervious Area for an Urban Indian Catchment

AbstractDetermination of imperviousness, which is defined by total impervious area (TIA) and effective impervious area (EIA), is mandatory for hydrological modeling of water quantity and quality in urban areas. The determination of TIA is relatively easy and preferred to determination of EIA, even though the latter is considered to be more appropriate for hydrological studies. Accurate and representative determination of EIA requires knowledge of drainage network connectivity with the impervious surface, which cannot be ascertained from remote sensing data alone. A more realistic semiautomated direct method is suggested in this study to determine EIA by integrating the remote sensing data, the digital format of the drainage network, and a digital elevation model (DEM) of the study area. Based on the results obtained from the proposed method, a power relationship [EIA=0.0035×(TIA)2.17] relating easily measurable TIA and hydraulically relevant EIA was determined for an ungauged urban catchment in northeast ...

The use of a flood index to characterise flooding in the north-eastern region of Bangladesh

Flooding in the Haor region in the north-east of Bangladesh is presented in this paper. A haor is a saucershaped depression, which is used during the dry period (Dec to mid-May) for agriculture and as a fishery during the wet period (Jun-Nov). Pre-monsoon flooding till mid-May causes agricultural loss. The area is bordering India, and is fed by some flashy Indian catchments. The area is drained mainly by the Surma-Kushiyara river system. The terrain generally is flat and the flashy characteristics die out within a short distance from the border. Limited studies on the region, particularly with the help of numerical models, have been carried out in the past. Therefore, an objective of the current research was to set up numerical models capable of reasonably emulating the physical system. Such models could, for example, associate different gauges to the spatio-temporal variation of hydrodynamic variables and help in carrying out a systemic study on the flood propagation. A 1D2D model, with one-dimensional model for the rivers (based on MIKE 11 from DHI) and a two-dimensional model for the haors (based on MIKE 21 from DHI) were developed. In order to characterize flooding in the large area a flood index is proposed, which is computed based on the hydrograph characteristics such as the rising curve gradient, flood magnitude ratio and time to peak. The index was used in characterising flooding in the Haor region. In general, two groups of rivers were identified. The study enabled identifying the hot-spots in the study area with risks from flooding.

Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance.

Effect of DEM source on equivalent Horton–Strahler ratio based GIUH for catchments in two Indian river basins

Summary Horton–Strahler (H–S) concept has been extensively used for quantification of characteristics of a stream network since several decades. The quantified values are often sensitive to threshold area specified for initiation of streams to demarcate the network, and to the position of outlet of a catchment. This implies that inferences drawn based on derived characteristics for a stream network are likely to be inconsistent, which is undesirable. To address this, a strategy based on self-similarity properties of channel network was proposed recently by Moussa (2009), which involves estimation of equivalent H–S ratios using catchment shape descriptors that are independent of threshold area. This study investigates effectiveness of the strategy on 42 catchments of various sizes in two Indian river basins (Cauvery and Mahanadi). Effect of digital elevation model (DEM) source on estimates of equivalent H–S ratios and characteristics of Geomorphologic Instantaneous Unit Hydrograph (GIUH) derived based on the same are examined by considering SRTM and ASTER DEMs. Results indicate that self-similarity assumptions are valid for the Indian catchments. Comparison of equivalent GIUH derived for each of the catchments based on real channel network with that derived using different DEM sources indicated differences that could be attributed to DEM-based uncertainty associated with estimates of: (i) equivalent H–S ratios that are functions of the self-similarity properties of channel network, and (ii) equivalent length of highest order stream that depends on self-similarity properties and configuration/characteristics of stream network. This uncertainty cannot be ignored in hydrological studies.

An experiment to gauge an ungauged catchment: rapid data assessment and eco-hydrological modelling in a data-scarce rural catchment

We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling.Editor Z.W. Kundzewicz; Associate editor F. Hattermann

Impact of Monthly Curve Number on Daily Runoff Estimation for Ozat Catchment in India

The Soil Conservation Service Curve Number (SCS-CN) is a well-established loss-rate model to estimate runoff. It combines watershed parameters and climatic factors in one entity curve number (CN). The CN exhibits an inherent seasonality beyond its spatial variability, which cannot be accounted for by the conventional methods. In the present study, an attempt has been made to determine the CN for different months of monsoon season with an objective to evaluate the impact of monthly CN on runoff estimation for Ozat catchment (Gujarat State, India). The standard CN and month wise CN were determined by three procedures, viz, the median, geometric mean and standard asymptotic fit using gauged rainfall and runoff. This study shows that the predictive capability of CN determination methods can be improved by using monthly CN. Refined Willmott’s index (dr) and mean absolute error (MAE) were used to assess and validate the performance of each method. The asymptotic fit CN method with monthly CN resulting dr from 0.46 to 0.49 and MAE from 1.13 mm to 1.18 mm was judged to be more consistent with the existing commonly used CN methods in terms of runoff estimation for the study area.

A combined bottom-up and top-down approach for assessment of climate change adaptation options

• We integrate stakeholder perceptions and modelling for robust adaptation planning. • High resolution RCMs and ensemble mean projections are used to force WEAP model. • Effect of stakeholder prioritized adaptation options on future streamflow analysed. • Increasing forest cover best address local climate change adaptation requirements. Focus of recent scientific research in the water sector has shifted from analysis of climate change impacts to assessment of climate change adaptation options. However, limited attention has been given to integration of bottom-up and top-down methods for assessment of adaptation options. The integrated approach used in this study uses hydrological modelling to assess the effect of stakeholder prioritized adaptation options for the Kangsabati river catchment in India. A series of 14 multi-level stakeholder consultations are used to ascertain locally relevant no-regret adaptation options using Multi-Criteria Analysis (MCA) and scenario analysis methods. A validated Water Evaluation And Planning (WEAP) model is then used to project the effect of three options; option 1 check dams (CD), option 2 increasing forest cover (IFC) and option 3 combined CD and IFC, on future (2021–2050) streamflow. High resolution (∼25 km) climatic projections from four Regional Climate Models (RCMs) and their ensemble based on the SRES A1B scenario for the mid-21st century period are used to force the WEAP model. Results indicate that although all three adaptation options reduce streamflow, in comparison with scenario without adaptation, their magnitude, temporal pattern and effect on high and low streamflows are different. Options 2 and 3 reduce streamflow percentage by an order of magnitude greater than option 1. These characteristics affect their ability to address key adaptation requirements and therefore, we find that IFC emerges as a hydrologically suitable adaptation option for the study area. Based on study results we also conclude that such an integrated approach is advantageous and is a valuable tool for locally relevant climate change adaptation policymaking.

Role of rainfall events and imperviousness parameters on urban runoff modelling

The volume and rate of storm water runoff in an urban watershed depend directly on the precipitation magnitude as well as its spatial and temporal distribution over the catchment. The runoff simulation may be on the basis of continuous or event wise rainfall data. Event wise simulation requires a minimum of one design-storm hyetograph as input. In contrast, continuous runoff modelling incorporates the entire meteorological record (days, months or years) of the watershed as the input. Many a time, due to the non-availability of short-interval rainfall data, a continuous simulation is performed. The present study predicts the runoff in an urban north-east Indian catchment based on event wise and continuous simulation. Continuous modelling has been performed by taking the daily rainfall data as input file. Storm water management model has been used for runoff simulation. This would help to understand the variations in urban runoff modelling due to an event based and continuous rainfall input. Green Ampt model has been used for infiltration modelling. A comparison is presented between the predicted runoff from the continuous and event wise rainfall data by considering different imperviousness parameters. The simulated runoff is overestimated by the total impervious area (TIA) that disregards the type of connectivity to the collecting network.

Modelling the impact of extensive irrigation on the groundwater resources

Drastic groundwater resource depletion due to excessive extraction for irrigation is a major concern in many parts of India. In this study, an attempt was made to simulate the groundwater scenario of the catchment using ArcSWAT. Due to the restriction on the maximum initial storage, the deep aquifer component in ArcSWAT was found to be insufficient to represent the excessive groundwater depletion scenario. Hence, a separate water balance model was used for simulating the deep aquifer water table. This approach is demonstrated through a case study for the Malaprabha catchment in India. Multi-site rainfall data was used to represent the spatial variation in the catchment climatology. Model parameters were calibrated using observed monthly stream flow data. Groundwater table simulation was validated using the qualitative information available from the field. The stream flow was found to be well simulated in the model. The simulated groundwater table fluctuation is also matching reasonably well with the field observations. From the model simulations, deep aquifer water table fluctuation was found very severe in the semi-arid lower parts of the catchment, with some areas showing around 60 m depletion over a period of eight years. Copyright © 2012 John Wiley & Sons, Ltd.

SEDIMENT YIELD ESTIMATION AND PRIORITIZATION OF WATERSHED USING REMOTE SENSING AND GIS

Abstract. Soil erosion is the greatest destroyer of land resources in Indravati catchment. It carries the highest amount of sediment compared to other catchment in India. This catchment spreading an area of 41,285 square km is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the present study, USLE is used to estimate sediment yield at the outlet of river Indravati catchment. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined. From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield at the out let of the catchment is 22.31 Million tons per year. The predicted sediment yield verified with the observed data. The Indravathi basin is divided into 424 sub-watersheds and prioritization of all 424 sub-watersheds is carried out according to soil loss intensity for soil conservation purpose. Generated soil loss map will be useful to soil conservationist and decision makers for watershed management. Overall 19.71 % of the area is undergoing high erosion rates which are a major contributor to the sediment yield (78.04 %) in the catchment. This area represents high-priority area for management in order to reduce soil losses, which are mostly found in upstream of the catchment. It is indicated that the areas of high soil erosion can be accounted for in terms of steep unstable terrain, and the occurrence of highly erodible soils and low vegetation cover.

ENERGY AND GREENHOUSE GAS EMISSION ACCOUNTING FRAMEWORK FOR GROUNDWATER USE IN AGRICULTURE

ABSTRACTChanges in energy subsidies for Indian agriculture and the introduction of a carbon tax in Australia have the potential to impact on energy use practices in groundwater‐irrigated agriculture in both countries. A general framework for the accounting of life cycle greenhouse gas emissions and life cycle energy consumption from groundwater‐irrigated agriculture was developed using life cycle and supply chain analyses to examine the contributing aspects of groundwater irrigation to total associated greenhouse gas emissions and energy use. The framework then formed the basis of a greenhouse gas emission and energy accounting model that was simulated for the groundwater‐ dependent agricultural areas of the Musi catchment in India and the south‐east region of South Australia. The region in South Australia was found to be emitting around twice the greenhouse gas of the Indian region per unit volume of water delivered, while emissions associated with operating electricity powered water pumps contributed more than 99.8% of modelled emissions in the south‐east of South Australia and over 99.1% of emissions in the Musi catchment. Diesel powered water pump irrigation systems emitted the least total amount of greenhouse gas emissions per unit volume of water supplied, compared to grid electricity and diesel generator powered submersible water pump options. Copyright © 2012 John Wiley & Sons, Ltd.

Genetic Algorithm Driven ANN Model for Runoff Estimation

Precipitation is the only data available in most of the Indian catchments for any hydrological study. For estimation of runoff at the outlet of the study catchment from India, daily precipitation for three years recorded at five raingauge stations is the base data collected. Artificial Neural Network (ANN) a data driven technique is utilised for modelling runoff. Input variables are selected by different filter as well as wrapper approaches. Mutual information criterion is found to be useful for the ANNs for the study area. ANN architecture is optimised by selection of transfer function, training algorithm, hidden layers, hidden neurons, initial weights. For ANN weights finalisation Genetic algorithm is utilised. The performance of ANN model is validated using more than ten performance criteria. The wholesome approach helps in reinforcing the use of data driven modelling for runoff studies.

Estimating the own-price elasticity of demand for irrigation water in the Musi catchment of India

► A new and superior method of estimating the demand for water and its resultant own-price elasticity of demand. ► Using an accepted method to determine the data on the willingness-to-pay for water in a catchment. ► Understanding that a range of elasticity estimates exist for water used in a catchment. ► Coming to terms with the fact that a significant quantity of the water used in irrigation is perfectly elastic. ► Yet for some uses, water is highly price inelastic. As irrigation water is an input into a production process, its demand must be ‘derived’. According to theory, a derived demand schedule should be downward sloping and dependent on the outputs produced from it, the prices of other inputs and the price of the water itself. Problems arise when an attempt is made to estimate the demand for irrigation water and the resulting own-price elasticity of demand, as the uses to which water is put are spatially, temporarily and geographically diverse. Because water is not generally freely traded, what normally passes for an estimate of the own-price elasticity of demand for irrigation water is usually a well argued assumption or an estimate that is derived from a simulation model of a hypothesized producer. Such approaches tend to provide an inadequate explanation of what is an extremely complex and important relationship. An adequate explanation of the relationship between the price and the quantity demanded of water should be one that not only accords with the theoretical expectations, but also accounts for the diversity of products produced from water (which includes the management practices of farmers), the seasons in which it is used and over the region within which it is used. The objective in this article is to present a method of estimating the demand curve for irrigation water. The method uses actual field data which is collated using the Residual Method to determine the value of the marginal product of water deployed over a wide range of crops, seasons and regions. These values of the marginal products, all which must lie of the input demand schedule for water, are then ordered from the highest value to the lowest. Then, the amount of irrigation water used for each product, in each season and in each region is cumulatively summed over the range of uses according to the order of the values of the marginal products. This data, once ordered, is then used to econometrically estimate the demand schedule from which the own-price elasticity of demand for irrigation water can be derived. To illustrate the method, the values of the marginal product of water deployed in the Musi catchment in India are used to determine an own-price elasticity of demand for irrigation water which has some positive value to producers of approximately −0.64. For water that is most highly valued, the elasticity was found to be highly elastic at −2.12, while less valued water used in agriculture was far more inelastic at −0.44. Finally, for almost 36% of water deployed in the catchment the elasticity was logically determined to be perfectly elastic.

Estimation of spatial patterns of soil erosion using remote sensing and GIS: a case study of Indravati catchment

Soil erosion is a serious environmental problem in Indravati catchment. It carries the highest amount of sediments compared with other catchments in India. This catchment spreading an area of 41,285 km2 is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the present study, USLE is used to estimate potential soil erosion from river Indravati catchment. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined. The derived soil loss map from USLE model is classified into six categories ranging from slight to very severe risk depending on the calculated soil erosion amount. The soil erosion map is linked to elevation and slope maps to identify the area for conservation practice in order to reduce the soil loss. From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield at the out let of the catchment is 22.30 Million tons per annum. The predicted sediment yield verified with the observed data.

Lead isotopes in groundwater as an indicator of water–rock interaction (Masheshwaram catchment, Andhra Pradesh, India)

This study reports on the lead geochemistry and Pb-isotope ratios of ground waters along a small (53 km 2) endoreic granitic catchment in India (Masheshwaram, Andhra Pradesh). The main focus is on granitic parent rock composition, water chemistry and isotope tracing, through the determination of lead isotopes in water by Multi-Collector ICP-MS using an improved new procedure. This method is efficient to give reliable Pb-isotope ratios with uncertainties (i.e. lower than 0.3% on each 206Pb, 207Pb, 208Pb ratios normalized to 204Pb) low enough to allow the different types of groundwater to be discriminated. Lead concentrations span over one or two orders of magnitude up to approximately 20 µg L − 1 . Pb isotopes fluctuate largely as exemplified by the 206Pb/ 204Pb ratio, ranging from 17.01 up to 25.35. Most of the lead in the ground waters is of geogenic origin, and through the lead isotopic signature in groundwater, we have traced and fingerprinted the processes of water–rock interaction considering the granite matrix. Combining a weathering model and field observations, we were able to define a two step weathering process that includes a control on the Pb-isotope ratios by accessory phases and by the main mineral from the granite in a second step of weathering.