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AN ANALYTICAL STUDY ON RIVERBED AND RIVERBANK FILTRATION

2015-06-01T00:00:00Z

Title: AN ANALYTICAL STUDY ON RIVERBED AND RIVERBANK FILTRATION Authors: Bishnoi, Kailash Abstract: Surface water as a source of drinking water requires costly treatment to make it free from physical, chemical, and bacteriological contamination. Therefore, the managers of various water utilities are exploring the other sources, wherein, the cost of treatment is low. Groundwater is considered as a sustainable source of drinking water in many parts of the world as it requires minimal treatment. Most of the urban areas are located on the banks of the river which are generally contaminated due to various anthropogenic activities. Rivers are the main source of water supply to various cities especially in the Indo-Gangetic plain. In such cases, as the rivers are mostly polluted, it results in heavy treatment cost. Therefore, in such situations, water collected through a collector pipe laid under a riverbed or through a radial well constructed adjacent to the river is a better choice. The flow through collector pipes in such cases shall be free from suspended particles as well as from bacterial contamination as the riverbed/ riverbank filtration work as slow sand filter. Riverbank filtration (RBF) is a process during which surface water is subjected to subsurface flow prior to extraction from the wells. In RBF process, surface water is subject to a combination of physical, chemical, and biological processes such as filtration, dilution, sorption, and biodegradation that significantly improve the raw water quality. RBF is widely used for drinking water purposes as the water utilities strive to meet increasingly stringent drinking water regulations, especially with respect to the provisions of multiple barriers for protection against microbial pathogens and tighter regulations related to Disinfestation By Products (DBPs). It has been noticed that only a few studies have been carried out to model such systems mathematically which resulted in analytical solutions. In this study, an attempt has been made to analyse the system of riverbed and riverbank filtration mathematically and to derive the analytical solutions corresponding to various flow characteristics under steady flow condition through such a system. A radial collector well, commonly known as "Ranney Well", collects water from underground aquifer through slotted radial pipes extended horizontally outward from a caisson. Like infiltration galleries, they are located in or close to rivers and other surfacewater bodies. A collector pipe is the primary component of a radial collector well constructed either for riverbed or riverbank filtration. Assuming the collector pipe as a line sink and applying the conformal mapping technique, Aravin and Numerov (1965) have derived an analytical solution for computing potential and flow to the collector pipe laid under riverbed under steady state flow condition. They have considered the origin of the physical domain at the centre of the collector pipe, which restricts the convenience of analysis. In this study, the origin of the physical flow domain is considered at the lower impervious base of the aquifer, which makes the analysis easier as compared to Aravin and Numerov (1965). Analytical expressions have been derived for the potential at different location in the flow domain, quantity of flow to the collector pipe, entrance velocity, and travel time of a parcel of water from the riverbed to the collector pipe along the shortest path. Further, using the travel time and the logistic function approach, the number of log cycle reduction in bacterial concentration has been found out. It has been noticed that this expression is non-linear in nature which depends on the reproduction and decay rate of microorganisms. Based on the dimensionless parameters obtained and the analysis related to flow characteristics, following conclusions are drawn: Yield of a collector pipe is linearly proportional to hydraulic conductivity of the riverbed material, drawdown in the well caisson, length of the collector pipe, and Nonlinearly dependent on the diameter of the collector pipe, thickness of the aquifer, height above the impervious base at which the collector pipe laid. Further, the present study has been extended to two more cases, i.e., assuming the collector pipe as a line slit, and collector pipe with a square cross-section having constant finite head boundary condition at their periphery. In both the cases, collector pipe is laid under fully penetrating riverbed. It is found that whether the collector pipe is assumed as a line sink with infinite head boundary or as a line slit or as a collector pipe with square cross-section with finite head boundary; there is no appreciable difference in the estimated flow to the collector pipe. In case of riverbank filtration, Zhan and Cao (2000) have put forward the philosophy that during late pumping stage, horizontal pseudo-radial flow takes place towards a horizontal collector pipe. This postulation supports the assumption of sheet flow condition in a thin aquifer system with horizontal collector pipe(s). In the present study, using this philosophy for applying Schwartz-Christoffel conformal mapping technique, radial collector well systems having several coplanar laterals located near a straight river reach have been analyzed. The collector well systems with different lengths of laterals, orientation of laterals and distance of the collector well from the river, etc, have been analyzed for safe yield. In case of a collector well with 4 laterals of equal length, it has been found that the - maximum flow occurs when angle between the laterals oriented towards the river is and it for <5 (see Fig. 5.2 (a)). For > 5 , flow to the collector well is maximum for y = 0.5. A radial collector well with 3 radials is a particular case of 4 laterals in which one of the collectors (13) (which is perpendicular to the river axis but away from river) is zero. The flow It in such well system is maximum, if the other two laterals are oriented at an angle y = 0.5 for R1 2 <5. For - > 5, the flow to the collector well is maximum if y = %'. In case of a collector well with three radials of equal length in which one of them orient away from the river, the other two should be oriented at an angle 0.2 :!~ y :5 X for < 5 to obtain near 12 maximum yield. For R > 5, their orientation should be 12 , :5 ' :!~ In order to validate the results using the concept of sheet flow, an exact solution of flow computation to a line sink in a confined aquifer with collector pipe laid parallel to the river is suggested. In the study, using the conformal mapping technique, an exact analytical solution for two-dimensional flow in vertical plane normal to a collector pipe laid parallel to a fully penetrating river in the middle of a confined aquifer is obtained. While estimating flow to a radial collector well with sheet flow condition, the thickness of aquifer and diameter of the collector pipe are not considered. Therefore, in order to account for thickness of the aquifer, it is suggested to multiply the estimated flow by the thickness of aquifer. As the flow does not increase linearly with thickness of the aquifer, a correction factor needs to be applied. It has been found that the correction factor increases marginally as the thickness of the aquifer decreases. It decreases as the distance of the collector pipe from the riverbank increases. It has been noticed that as the correction factor is very much less than 1, Broom's postulation 0 =-kD(~Iy_ + + C of flow estimation using sheet flow concept overestimates the collector pipe yield, and hence need a correction factor. It may be noticed that the derived correction factors may be applied to estimate the collector well yield with more than 2 collector pipes. Further, yield of collector well increases as it is located nearer to the water body but will decrease the travel time and hence the number of log cycle reduction. It also increases with increase in length and diameter of the collector pipe.

HYDROLOGICAL MODELLING OF A TROPICAL WATERSHED UNDER LAND USE AND CLIMATE CHANGE SCENARIOS

2019-12-01T00:00:00Z

Title: HYDROLOGICAL MODELLING OF A TROPICAL WATERSHED UNDER LAND USE AND CLIMATE CHANGE SCENARIOS Authors: Chandrakar, Ayush Abstract: Water is one of the essential components of our environment. Therefore, proper planning and management are essential to achieve sustainable utilization. Changes in climate and land use have significantly altered the hydrological cycle which in turn has affected the water resources. Due to increased uncertainty in both climate and land-use change projections, improved knowledge of watershed hydrology and resource availability are indispensable for current and future policy formulation and sustainable development of the water sector. The present study has been carried out to ascertain the availability of water and its distribution under the impact of climate change projection and anthropogenic intervention in the Kharun watershed, India. This study investigated the changes in water balance components under varied land use and climate change projections over the Kharun watershed. Kharun watershed lies in the tropical region of central India. Trend changes in meteorological parameters of the past and the future constituted the climate change aspect of the study. The land use land cover (LULC) change dynamics constituted the anthropogenic intervention aspect of the study. Keeping into account the changes in climatic conditions and land change patterns, a hydrological impact assessment was carried out over the study area. Trend analysis is one of the most significant tools to analyze the global warming problem as it quantifies the past and future changes in meteorological and hydro-climatological parameters. In the present study, trend detection was carried out for two metrological parameters namely, long term temperature (maximum, minimum and mean) and precipitation using regression analysis and Modified Mann-Kendall (MMK) test. The magnitude of change was estimated using the Sen’s slope estimator over 22 grids in and around the study area. Cumulative sum (Cusum) and sequential Mann-Kendall (SQMK) test was used to identify the climatic shift (change per year) over the meteorological time series. Significant findings of the study stated an increase in average maximum temperature during summer (0.19⁰C), post-monsoon (0.21⁰C), and winter (0.61⁰C) seasons. A significant reduction in average yearly minimum temperature (-0.68⁰C) was also observed. The annual precipitation decreased by almost 210 mm over 115 years. Similar statistics were computed over 23 indices of meteorological extremes derived from long term precipitation and temperature time series. Out of these 23 indices, five were proposed in the study ii based on the precipitation intensity indices suggested by India Meteorological Department (IMD). Long term trend changes in these indices were computed for both historical as well as future periods. For reproduction of meteorological parameters in order to study changes in extreme value indices in the future, regional climate model (RCMs) were evaluated. Four RCMs were identified as the most suitable models to determine future times series data of precipitation and temperature (maximum and minimum) for the study viz. CCCma, CSIRO, MIROC5 and NorESM. The distribution mapping technique was used to remove systematic biases present in the data. MMK test statistic was used to evaluate the presence of any trend while the magnitude of the trend was quantified using Sen’s slope estimator over the entire period (2011-2100) and for three climate periods, namely CC1 (2011-2041), CC2 (2041-2070) and CC3 (2071-2100). These tests were applied over two scenarios viz. RCP 4.5 and RCP 8.5. After the computation of long term variation in meteorological extremes, it can be inferred that the gap between the minimum and maximum temperature is increasing over the study period at an average rate of 0.09⁰C/decade (4.6%), which explains the increasing trend in Diurnal Temperature Range (DTR). This precisely precedes the fact that the days are getting hotter, and the nights are getting colder and its effects can be seen over the rainfall intensities in the region. As per the results obtained, there is a reduction observed in the number of light rainy days (-10.2%), moderate rainy days (-17.8%) in contrast to heavy and heavy rainy days (-25.5 and -18.4%). The number of cumulative dry days in the study area has also increased by 19.5%, which explains the reduction in rainy days. The overall result indicates an increase in DTR in the future along with an increase in days with heavy rainfalls in the case of both scenarios for the study area. Evaluation of land use land cover is critical and must be monitored to assess the impact on the environment. For this purpose, LULC mapping was carried out for the region using satellite imageries (LANDSAT 5, 7, and 8), remote sensing (RS), and geographical information system (GIS) tools. The LULC maps were classified into six different classes namely water bodies, urban areas, agricultural land, barren land, mixed forest, and sand/open rocks. Significant findings in the study state a decrease in vegetation (agricultural land and mixed forest) in the region due to the rise in the urban area and barren land. After the analysis of historical trend patterns in LULC, the land use land cover map for the near future (2030) was projected using the CA-Markov model. The model was validated and simulated with the classified LULC map of 2015. The projected LULC map of 2030 iii indicated the continuation of the same trend of the past. These future projections indicate the expected changes in the near future. Therefore, the LULC changes concerning different classes in the near future will help in cautioning the concerned authorities for proper planning and management of the study area. In order to investigate the effect of land use land cover change and historical and future climate variability on water availability of Kharun watershed, Soil and Water Assessment Tool (SWAT), a semi-distributed hydrological model was calibrated and validated for the area. Parameters namely Baseflow Alpha Factor (ALPHA_BF), Plant uptake compensation factor (EPCO), and Deep aquifer percolation fraction (RCHRG_DP), were found to be the most sensitive parameters for the Kharun watershed. For monthly simulations, the values of Coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), and Percent bias (PBIAS) were found to be 0.84, 0.8, and -9.4% during calibration, and 0.85, 0.79 and -9.2% during validation respectively. The results indicated a very good model performance for Kharun watershed. Based on these results, it is concluded that the SWAT model can be successfully employed for the hydrological simulation purposes over Kharun watershed. In order to compute the hydrological components under the dynamics of land use land cover and climate change, 29 simulations were carried out under different variations of land use and climate parameters. Results indicated that the increase in settlement (urban and barren land) for real estate development, accompanied by a decrease in vegetation (agricultural land and mixed forest), has resulted in an increased water yield but the evapotranspiration (ET) reduced due to reduction of vegetation. It is observed that ET reduced with time due to a decrease in vegetation, earlier it used to be 326.71 mm in 1990 but it declined to 298.39 mm during the projected the year of 2030. Due to an increase in overland flow, the water yield increased from 781.58 mm in 1990 to 881.84 mm in the projected the year of 2030. During the last two decades (2010-2030), LULC change increased water yield by 45.88 mm and accounted for 5.48% of the total change (881.84 mm). Moreover, ET decreased by 4.19% in the same duration. Reduction in precipitation was observed for both RCP scenarios in the period CC1 (2011-2040) by -16.83% for NorESM and by -16.29% for MIROC5. The simulation result suggests that the evapotranspiration (ET) in the region is going to increase between 2011 and 2100 but when compared to IMD simulation as a reference, it was observed that the ET has decreased. The maximum change in ET was obtained in CC3. For RCP 4.5, it was 3.99% (MIROC5) and for RCP 8.5, it was 7.26% (MIROC5). While the minimum change iv in ET was observed in CC1. The maximum increase in water yield was observed in CC3, 37.36% for CSIRO (RCP 4.5), and 77.10% for CCCma (RCP 8.5). In summary, the study provided a scientifically essential and practically relevant approach towards identifying the historical climate variability and hydrological assessment under land use and climate change scenarios considering representative climate models output, in contributing to water resources planning and management in the context of a small tropical watershed.

INVESTIGATION OF SCS-CN METHODOLOGY ON EXPERIMENTAL PLOT AND CATCHMENT SCALES

2018-10-01T00:00:00Z

Title: INVESTIGATION OF SCS-CN METHODOLOGY ON EXPERIMENTAL PLOT AND CATCHMENT SCALES Authors: Lal, Mohan Abstract: Runoff is one of the most important variables used in planning and design of hydraulic structures and assessing the water yield potential of a watershed. Runoff is a function of many variables such as rainfall duration and intensity, soil moisture, land use/land cover, soil infiltration capacity, watershed slope etc. There are a number of models available in literature considering different variables governing the surface runoff. Among them, the lumped conceptual models are quite useful for simple yet realistic analyses. The Natural Resources Conservation Service curve number (NRCS–CN) formerly known as the Soil Conservation Service curve number (SCS–CN) method is the most popular method to determine the storm event runoff from an ungauged small watershed for a given amount of rainfall. The SCS-CN method was developed in 1954. It is documented in Section 4 of the National Engineering Handbook (NEH-4) published by the Soil Conservation Service (now called the Natural Resources Conservation Service), United States. Department of Agriculture in 1956. The document has since been revised several times. The SCS-CN method is the result of exhaustive field investigations carried out during 1930s and 1940s. The method has since then witnessed myriad applications world over. It is one of the most popular methods for computing the surface runoff for a given rainfall event from small agricultural, forest, and urban watersheds. It is simple, easy to understand and apply, stable, and useful for ungauged watersheds. Due to its low input data requirements and simplicity, many erosion, hydrologic, and water-quality models have employed this method for determination of runoff. The primary reason for its wide applicability and acceptability lies in the fact that it accounts for most runoff producing watershed characteristics: soil type, land use/treatment, surface condition, and antecedent moisture condition. The only parameter of this methodology, i.e. the Curve Number (CN), is crucial for accurate runoff prediction. Based on exhaustive field investigations carried out in the United States, curve numbers were derived for different land uses, soil types, hydrologic condition, and management practices and these are reported in NEH-4. These numbers have seldom been verified for Indian watersheds. Evidently, most studies have concentrated on the application of the existing SCS-CN method utilizing CN derived from NEH-4 tables. No systematic effort appears to have been made for evaluating the SCS-CN methodology experimentally, particularly for Indian watersheds, which invokes the need of the study. The aim of present research was to enhance the understanding of SCS-CN methodology by investigating its different parameters employing naturally observed P-Q datasets. This study covers relative accuracy of different CNs VI determination methods and comparing them with NEH–4 tables CN values; evaluating the effect of initial abstraction coefficient and antecedent moisture on CN and runoff; evaluation of existing AMC–dependent CN formulae, which are otherwise developed using United States datasets. The AMC–dependent CN formulae incorporating initial abstraction coefficient effect is also tested for enhancing runoff estimation. The present study uses the rainfall (P)–runoff (Q) dataset of various climatic settings. Locally measured and published literature data have been used in the investigation of different parameters of SCS-CN methodology. For locally monitored data, the natural P–Q events were captured on 35 plots of 22m length and 5m width having different slope (5%, 3%, and 1%), land use (agricultural land use: Sugarcane, Maize, Black gram, Fallow land, Lentil, and Chana), and hydrologic soil group (HSG) during August 2012–April 2015 (or three crop growing seasons in study area) for the experimentation work carried out at Roorkee, India. The experimental field (Lat.: 29° 50′ 09″ N and Long.: 77° 55′ 21″ E) is situated at the right bank of Solani River, a tributary of Ganga River, the largest river basin in India. Precipitation was recorded with the help of Tipping Bucket rain gauge and a non-recording rain gauge installed within the experimental site. The surface runoff generated during rain storms was collected in separate chambers equipped with multi-slot divisor (5-slot) (1m × 1m × 1m) constructed at the downstream end of each plot and the variation in depth of water stored with respect to time was monitored regularly, but manually. Infiltration tests were conducted for each plot using the double ring infiltrometer. Soil water measurements were taken by time domain reflectometry (TDR) probe of the ‘Fieldscout TDR-300’. Besides, the published literature P-Q data were collected for 36 plots/watersheds having different size, land use, slope and soil consisting heterogeneous climatic conditions. The rainfall (P)runoff (Q) behaviour pattern was analysed using naturally observed PQ data from experimental study plots located at Roorkee site and it was found that nonlinear variation of runoff coefficient (Rc) with P is similar to the variation of Q with P, but the correlation between Rc and P is much lower than that between Q and P. As expected, the mean runoff coefficient (Rcm) was higher for the plots having HSGs C followed by B and A. The concept of runoff initiation threshold (I) also called rainfall threshold for runoff generation confirms the runoff generation phenomenon of generating low runoff from lighter soils as the values of I was highest for HSGs A followed by B and C. These finding indicates that HSG (or indirectly soils infiltration capacity, fc) seems to play a major role in controlling runoff in the plots. The KruskalWallis (KW) test analysis performed to analyse the effect of land use, soil VII type, and plot slope on Q (or Rc) show that, Q is more significantly influenced by soil type rather than land uses or slopes as fc is the main explanatory variable for runoff (or CN) production in the study plots. In present study experimental plots, CN is inversely related to fc, which supports the applicability of NEH4 tables CNs declining with fc (or HSG). Further to check the dependency of observed CN on in-situ antecedent moisture content, CN (or, potential maximum retention, S) values showed a higher degree of dependence on the physically observed 1-day antecedent soil moisture (θo1) than other duration antecedent soil moisture values. The performance of eight different CN estimation methods, viz. storm event mean and median, rank-order mean and median, log-normal frequency, S-probability (SP), geometric mean and least square fit, was evaluated using P–Q data measured on small agricultural plots located in India. The KruskalWallis test multiple comparison analysis show that there was no single method which has produced significantly higher (or lower) CNs than other. The least square fit method was observed to estimate significantly lower CN than other methods except log-normal frequency method. Based on the overall score and ranking system calculated from different goodness of fit indices, the method performance in runoff estimation was as follows: S-probability > geometric mean > storm event mean > rank-order median > rank-order mean > least square fit > storm event median > log-normal frequency. The comparison of observed P-Q data based CNs with tabulated CNs show that, on the whole, the CN estimates from NEH-4 tables do not match those derived from observed P–Q dataset. As a result, the runoff prediction using former CNs was poor for the data of experimental plots of Roorkee site. However, match was little better for higher CN values, consistent with general notion that the existing SCS-CN method performs better for high P–Q (or CN) events. The reason for tabulated CNs to have performed most poorly is that these are the generalized values derived from the watersheds of United States, consistent with the results of other studies. The plot-data optimization yielded initial abstraction coefficient (λ) values ranging from 0 to 0.659 for ordered dataset and 0 to 0.208 for natural dataset (with 0 as the most frequent value for both datasets). Mean and median λ values were, respectively, 0.030 & 0 for natural P– Q dataset and 0.108 & 0 for ordered P–Q dataset, quite different from standard λ =0.2, but consistent with the results of other studies carried out elsewhere. Notably, the existence of Ia-S relationship for different plots was also investigated; and in contrast to the existing notion, Ia when plotted against S exhibited no correlation for both natural and ordered datasets, consistent with the findings of Jiang (2001). Runoff estimation was very sensitive to λ and it improved consistently as  changed from 0.2 to 0.03. Compared to traditionally assumed λ=0.2, a refined VIII λ=0.03 is recommend for the use in regions of similar to study site. Further, a relationship between CN0.20 (λ = 0.20) and CN0.03 (λ = 0.03), useful for CN conversion for field application is established. It is well established phenomenon that accurate estimation of the surface runoff is one of the most important bases for planning and management of water resource systems and environmental quality assessment of water and soil. Therefore, in popular SCS–CN method, correct estimation of AMC–dependent CN values is always necessary. Since CNs varies with climatic condition of watersheds, there is need of using AMC-dependent CN-formulae developed utilizing data of watersheds having heterogeneous climatic conditions. The formulae developed from heterogeneous and large data sets will tend to have wider applicability. The present work evaluated the five existing (Arnold et al. 1990; Chow et al. 1988; Hawkins et al. 1985; Mishra et al. 2008b; Sobhani 1975) and three proposed (MC6, MC7, MC8) CN-AMC formulae. For developing the proposed formulae, CNs were derived for datasets from a large number of naturally observed P–Q events for an agricultural field located at Roorkee, Uttarakhand, India and available published data around the globe using standard initial abstraction ratio (λ) values as 0.20 and 0.030. The analysis shows that the existing Hawkins et al. (1985) formulae performed the best for conversion of CN2 into CN1 and CN3, when tested on NEH–4 AMC defining Tabular CNs considered as targeted values. It might be because the existing formulae were derived from the same datasets used as targeted values (i.e. NEH–4 AMC defining tables). However, all the three proposed MC6, MC7, and MC8 were best of the existing formulae in their application to field data. MC8 incorporating the effect of λ = 0.030 performed the best of all, and MC7 and MC6 better than the other existing formulae. Among the existing formulae, Mishra et al. (2008b) was superior followed by Hawkins et al. (1985). A comparison of the results derived from the eight different methods concluded that the MC8 formula that incorporates the effect of λ into standard SCS–CN method showed a superior performance in runoff simulation than the others. Since the proposed formulae performed the best in field application, these are recommended for field use to improve the accuracy of SCS–CN model. Keywords: Agricultural field; Curve number; Antecedent moisture condition; Runoff; NEH-4 Table; SCS-CN; NRCS-CN; Initial abstraction coefficient; Infiltration capacity.

HYDROLOGICAL MODELING TO STUDY THE INTERACTIONS OF LAND USE−CLIMATE−HYDROLOGY FOR SUSTAINABLE RIVER BASIN MANAGEMENT

2018-12-01T00:00:00Z

Title: HYDROLOGICAL MODELING TO STUDY THE INTERACTIONS OF LAND USE−CLIMATE−HYDROLOGY FOR SUSTAINABLE RIVER BASIN MANAGEMENT Authors: Subhash, Palmate Santosh Abstract: Sustainable natural resources management at local and regional scale is a prime concern for growth, development, conservation, and protection of the environment, and prosperity of the nation. To mitigate the present and future anthropogenic activities and climatic change, field-based investigations of land and water resources are time-consuming and challenging to manage and sustain the agriculture food production in developing countries like India. Indian River basins are one of the most influencing natural systems owing to land dynamics and the uncertain climatic events, such as cloud bursting and heavy rainfall occurred in Uttarakhand during the year 2013, then in Chennai (2015), and the recently in Kerala (2018). The present study has been focused to model the complex hydrological process of the Betwa River basin, part of the lower Yamuna River basin located in central India, for sustainable management of land and water resources considering future climate change and land use change. In this context, hydrological modelling can be considered as a valuable technique for the simulation of basin-wide various hydrologic components i.e. stream flow (FLOW), sediment yield (SYLD), evapotranspiration (ET) and water yield (WYLD) etc. In this study, various satellite imageries have been utilized to prepare the historical land use/land cover (LU/LC) maps for the years 1972, 1976, 1991, 2001, 2007, 2010 and 2013 using a maximum likelihood supervised classification method. Further, an integrated Cellular Automata-Markov Chain (CA-MC) model based on Geographical Information System (GIS)-based Multi-Criteria Evaluation (MCE) and the Multi-Objective Land Allocation (MOLA) methods has been employed to predict the future LU/LC maps for the years 2020, 2040, 2060, 2080 and 2100. Future problems such as food security and surface water resources availability are successfully discovered through CA-MC model. To study the relationships between land cover dynamics and hydro-climatic variables, the MODIS NDVI (MOD13Q1) and land cover (MCD12Q1) time-series datasets have been used for correlation analysis, and then Multiple Linear Regression (MLR) models were prepared at monthly, seasonal and annual time-scale over the period of 2001-2013. The Savitzky-Golay filtering method was employed to de-noise and smoothing of the NDVI time-series data using TIMESAT software. The land greening and land degradation under dry spell, wet spell and combined dry and wet spells were analyzed employing a conceptual framework, representing four concepts of climatic greening, climatic degradation, non-climatic greening and non-climatic degradation etc. The developed conceptual framework approach can be applied effectively in other river basins having different land cover and hydro-climatic conditions. Further, hydrological modelling considering numerous medium to large sized water storages (7 reservoirs and 2 weirs) located on main channel as well as tributary channel of the Betwa river has been carried out using the Soil and Water Assessment Tool (SWAT). With the required spatial, storage and outflow information, these water storages were successfully implemented and managed for reliable hydrological simulation using the SWAT model. Monthly calibration, validation, sensitivity and uncertainty analyses have been carried out using the SWAT- Calibration and Uncertainty Programs (CUP) Sequential Uncertainty Fitting version-2 (SUFI-2) algorithm for the years 2003-2013. The observed and simulated hydrographs for both the streamflow and sediment indicates a good performance of the SWAT model. The model ii performance was high for the Garrauli gauging site without any upstream water storage structure, as compared to the gauging sites with upstream water storage structures. This analysis shows that better information of the water storage structures promises a significantly improved hydrological simulation using the SWAT model. The India Meteorological Department (IMD) data benchmarked in calibrated and validated SWAT model was replaced by the downscaled and bias-corrected (quantile mapping method) Global Climate Model (GCM) data of the Max-Planck-Institute-Earth System Model-Medium Resolution (MPI-ESM-MR) model. In this study, the MPI-ESM-MR model data of RCP 8.5, a worst-case climate scenario, has been considered for hydrologic simulation at the severe climate condition in future. Land use data of the years 2013 and 2040, and the GCM-derived climate variables were categorized into five periods i.e. baseline 1986 (1986-2005), horizon 2020 (2020-2039), horizon 2040 (2040-2059), horizon 2060 (2060-2079), and horizon 2080 (2080-2099) and used to assess the land use and climate change impact on hydrological simulation of streamflow (FLOW), sediment yield (SYLD), Evapotranspiration (ET) and water yield (WYLD). It was found that climate change impact is dominant over the impact of land use change in future. Further, a conceptual framework has been developed to assess the individual as well as combined impacts of land use and climate change. The proposed conceptual framework can be used effectively for watershed analysis with given limitations. Furthermore, based on the future simulations, critical sub-watersheds of the study area were identified and then prioritized for effective implementation of Best Management Practices (BMPs). In this study, the over-land as well as in-stream BMPs has been implemented to reduce the streamflow and sediment yield in future. Four over-land BMPs namely tillage management, contour farming, residue management and strip cropping for agriculture land, and five in-stream BMPs namely grassed waterways, streambank stabilization, grade stabilization structures, porous gully plugs and recharge structures for main and tributary river channels have been considered in this study. Sensitivity and uncertainty analysis of BMPs parameters were also carried out for an effective management and implementation of BMPs in the river basin. The effectiveness of BMPs implementation was estimated by percent reduction and sensitivity index of the model parameters. It was found that strip cropping is the most effective agriculture land operation which reduces streamflow in the range of 11.07% to 13.97% and sediment yield in the range of 21.04% to 37.28% for soil and water conservation of the river basin in future. Furthermore, the in-stream BMPs namely grassed waterways and streambank stabilization can be an effective intervention for sediment yield reduction (about 20% to 60%), and grade stabilization structures for streamflow reduction (about 6% to 10%) within the main river channel. Overall, this study provides connectivity of land use change, climate change, and hydrological modelling for the research communities focusing sustainable river basin management, and may also provide valuable guidelines to the users interested in water resources development, planning and management in agriculture dominant large river basin.