scholarly journals A remote sensing-based approach for water accounting in the East Rapti River Basin, Nepal

2011 ◽  
Vol 7 (9) ◽  
pp. 15-30 ◽  
Author(s):  
Rajendra Lal Shilpakar ◽  
Wim G.M. Bastiaanssen ◽  
David J. Molden
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
River Basin ◽  
River Flow ◽  
Riparian Forest ◽  
Meteorological Data ◽  
Irrigated Agriculture ◽  
International Water Management Institute ◽  
Water Accounting ◽  
Mountainous River

Accurate estimates of evapotranspiration across different land uses are a major challenge in the process of understanding water availability and uses in a river basin. This study demonstrated a remote sensing-based procedure for accurately generating evaporative depletion and runoff in mountainous areas using Landsat ETM+ images combined with standard hydro-meteorological data. The data was used as a key input into the International Water Management Institute (IWMI)’s water accounting procedure to understand how water is now used, and opportunities for improvements in the future. We found a higher annual actual evapotranspiration from the riparian forest than from irrigated agriculture in the East Rapti River basin of Nepal. Another important finding of our study is that simple rainfall surplus can be a good predictor of river flow at an ungagged site of the East Rapti River basin. The water accounting analysis revealed that there is the potential for further development of water resources in the East Rapti River basin as only 59% of the total available water is depleted. A critical analysis of social and ecological flow requirements downstream is necessary before any development of water resources upstream. This study successfully demonstrated that the key inputs required for evaluating and monitoring the overall water resources conditions in a mountainous river basin can be computed from satellite data with a minimal support from ground information.DOI: http://dx.doi.org/10.3126/hjs.v7i9.5785 Himalayan Journal of Sciences Vol.7 Issue 9 2011 pp.15-30

scholarly journals Attribution of Long-Term Evapotranspiration Trends in the Mekong River Basin with a Remote Sensing-Based Process Model

2021 ◽  
Vol 13 (2) ◽  
pp. 303
Author(s):  
Shi Hu ◽  
Xingguo Mo
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Solar Radiation ◽  
River Basin ◽  
Mekong Delta ◽  
Mekong River ◽  
Catchment Management ◽  
Mekong River Basin ◽  
Area Index ◽  
Available Water

Using the Global Land Surface Satellite (GLASS) leaf area index (LAI), the actual evapotranspiration (ETa) and available water resources in the Mekong River Basin were estimated with the Remote Sensing-Based Vegetation Interface Processes Model (VIP-RS). The relative contributions of climate variables and vegetation greening to ETa were estimated with numerical experiments. The results show that the average ETa in the entire basin increased at a rate of 1.16 mm year−2 from 1980 to 2012 (36.7% of the area met the 95% significance level). Vegetation greening contributed 54.1% of the annual ETa trend, slightly higher than that of climate change. The contributions of air temperature, precipitation and the LAI were positive, whereas contributions of solar radiation and vapor pressure were negative. The effects of water supply and energy availability were equivalent on the variation of ETa throughout most of the basin, except the upper reach and downstream Mekong Delta. In the upper reach, climate warming played a critical role in the ETa variability, while the warming effect was offset by reduced solar radiation in the Mekong Delta (an energy-limited region). For the entire basin, the available water resources showed an increasing trend due to intensified precipitation; however, in downstream areas, additional pressure on available water resources is exerted due to cropland expansion with enhanced agricultural water consumption. The results provide scientific basis for practices of integrated catchment management and water resources allocation.

scholarly journals GIS and Remote Sensing Application in Water Management in Agriculture Field

2020 ◽  
Author(s):  
Sassi Mohamed Taher
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Resources ◽  
Land Surface ◽  
Remotely Sensed ◽  
Irrigated Agriculture ◽  
Accurate Information ◽  
Remotely Sensed Data ◽  
Gis And Remote Sensing ◽  
Practical Applications

This document is meant to demonstrate the potential uses of remote sensing in managing water resources for irrigated agriculture and to create awareness among potential users. Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere transfer processes can lead to a better understanding of the relationships between crop growth and water management. Remote sensing and GIS was used to map the agriculture area and for detect the change. This was very useful for mapping availability and need of water resources but the problem was concentrating in data collection and analysis because this kind of information and expertise are not available in all country in the world mainly in the developing and under developed country or third world country. However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing.

scholarly journals Comparing bias correction methods in downscaling meteorological variables for hydrologic impact study in an arid area in China

2014 ◽  
Vol 11 (11) ◽  
pp. 12659-12696 ◽  
Author(s):  
G. H. Fang ◽  
J. Yang ◽  
Y. N. Chen ◽  
C. Zammit
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Bias Correction ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Temperature Correction ◽  
Arid Area ◽  
Tarim River ◽  
Tarim River Basin ◽  
Impact Study

Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River Basin, Northwest China, and expected to be vulnerable to climate change. Regional Climate Models (RCM) have been proved to provide more reliable results for regional impact study of climate change (e.g. on water resources) than GCM models. However, it is still necessary to apply bias correction before they are used for water resources research due to often considerable biases. In this paper, after a sensitivity analysis on input meteorological variables based on Sobol' method, we compared five precipitation correction methods and three temperature correction methods to the output of a RCM model with its application to the Kaidu River Basin, one of the headwaters of the Tarim River Basin. Precipitation correction methods include Linear Scaling (LS), LOCal Intensity scaling (LOCI), Power Transformation (PT), Distribution Mapping (DM) and Quantile Mapping (QM); and temperature correction methods include LS, VARIance scaling (VARI) and DM. These corrected precipitation and temperature were compared to the observed meteorological data, and then their impacts on streamflow were also compared by driving a distributed hydrologic model. The results show: (1) precipitation, temperature, solar radiation are sensitivity to streamflow while relative humidity and wind speed are not, (2) raw RCM simulations are heavily biased from observed meteorological data, which results in biases in the simulated streamflows, and all bias correction methods effectively improved theses simulations, (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g. SD, percentile values) while LOCI method performed best in terms of the time series based indices (e.g. Nash–Sutcliffe coefficient, R2), (4) for temperature, all bias correction methods performed equally well in correcting raw temperature. (5) For simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with these of corrected precipitation, i.e. PT and QM methods performed equally best in correcting flow duration curve and peak flow while LOCI method performed best in terms of the time series based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other area and other models.

Development of a Non-Linear Integrated Drought Index (NDI) for Managing Drought and Water Resources Forecasting in the Upper Tana River Basin-Kenya

2020 ◽  
Vol 11 (1) ◽  
pp. 15-33
Author(s):  
Raphael Muli Wambua
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Lead Time ◽  
Drought Index ◽  
Meteorological Data ◽  
Principal Component ◽  
Drought Forecasting ◽  
Tropical River ◽  
Tana River ◽  
Non Linear

This article uses the non-linear integrated drought index (NDI) for managing drought and water resources forecasting in a tropical river basin. The NDI was formulated using principal component analysis (PCA). The NDI used hydro-meteorological data and forecasted using recursive multi-step neural networks. In this article, drought forecasting and projection is adopted for planning ahead for mitigation and for the adaptation of adverse effects of droughts and food insecurity in the river basin. Results that forecasting ability of NDI model using ANNs decreased with increase in lead time. The formulated NDI as a tool for projecting into the future.

scholarly journals Spatial Estimation of Reference Evapotranspiration in Andalusia, Spain

2008 ◽  
Vol 9 (2) ◽  
pp. 242-255 ◽  
Author(s):  
Karl Vanderlinden ◽  
Juan Vicente Giráldez ◽  
Marc Van Meirvenne
Keyword(s):  
Water Resources ◽  
Meteorological Data ◽  
Temporal Distribution ◽  
Spatial Optimization ◽  
Data Availability ◽  
Fine Tuning ◽  
Irrigated Agriculture ◽  
Estimation Errors ◽  
Secondary Information ◽  
Regional Water

Abstract Knowledge of the spatial and temporal distribution of reference crop evapotranspiration (ET0) is of interest for regional water resources management, especially in areas of the world where fine-tuning of agricultural water demands over large areas is required. This study provides a strategy for mapping ET0 in regions with low meteorological data availability. For Andalusia, Spain, it involves estimating ET0 from temperature data using a locally calibrated version of the Hargreaves equation and the application of geostatistical interpolation techniques that take into account elevation as secondary information. Average annual ET0 at 191 observatories (with elevation between 0 and 1260 m) ranged from 954 to 1460 mm, with an average of 1283 mm, a standard deviation of 99 mm, and a correlation coefficient with elevation of −0.86. Simple kriging with varying local means (SKlm) and kriging with an external drift (KED)—two methods that take into account elevation as secondary information—increased spatial model efficiency by 30% as compared to ordinary kriging. SKlm was used for mapping ET0 since it better reproduced the descriptive statistics of the point data and yielded slightly smaller root-mean-squared estimation errors than KED. The spatial correlation of annual and monthly ET0 was well structured and anisotropic. Short-range variability, for separation distances up to 20–40 km, showed a strong linear increase with distance while long-range variability, up to 130–250 km, increased more gently with distance. The results of this structural analysis are relevant for the spatial optimization of a recently installed automated ET0 observation network, while obtained maps constitute a valuable tool for regional water resources evaluation, planning, and management and contribute to optimizing water use in local irrigated agriculture.

scholarly journals ESTIMATING CONTRIBUTION OF WATER FLOW COMPONENTS TO KAMENG RIVER BASIN USING HYDROLOGICAL MODELLING

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 431-436
Author(s):  
S. Arora ◽  
A. V. Kulkarni ◽  
P. Ghosh ◽  
S. K. Satheesh
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Resource Management ◽  
Hydrological Cycle ◽  
Meteorological Data ◽  
Clean Energy ◽  
Coefficient Of Determination ◽  
Melt Water ◽  
Resilient Infrastructure ◽  
Discharge Profile

Abstract. The Himalayas, also known as third pole of the Earth feed some of the major rivers of the world viz. Ganga, Indus, Brahmaputra etc. The accurate assessment of water resources in eastern Himalayas is very important for respective policy makers. The detailed assessment of water resources and hydrological cycle component are very critical for attaining United Nations sustainable development goals (SDGs) such as affordable and clean energy, clean water and sanitation and building resilient infrastructure This study focuses on Kameng river basin, estimating the melt water & its contribution to the total discharge of the river. A 3-layer VIC model coupled with energy balance algorithm is used to estimate the patterns of melt and discharge profile in the region. Net contribution of melt water to the river were estimated to be about 18% during peak melt season in upper catchments. With advancement in technology, acquiring meteorological data via remote sensing has become more accurate & of high resolution. This data is one of the major inputs of the model. With accurate forecasting of these parameters, multipurpose hydropower projects in these regions can plan well in advance thus playing a major role in Integrated Water Resource Management. In current study the coefficient of determination & Nash-Sutcliffe efficiency were calculated to be 0.82 & 0.71 respectively. With increasing population in the region, any substantial change in the streamflow will have consequences unknown as of now, thus making this study a necessity & need of hour.

A Conceptual Framework for Modelling the Climate Change and its Impacts within a River Basin using Remote Sensing data

2020 ◽  
Author(s):  
Sathyaseelan Mayilvahanam ◽  
Sanjay Kumar Ghosh ◽  
Chandra Shekhar Prasad Ojha
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Warming ◽  
Conceptual Framework ◽  
River Basin ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Spatial And Temporal Scales ◽  
Process Component ◽  
Land Hydrology

<p><strong>Abstract</strong></p> <p>In general, modelling the climate change and its impacts within a hydrological unit brings out an understanding of the system and, its behaviour with various model constrains. The climate change and global warming studies are being under research and development phase, because of its complex and dynamic nature. The IPCC 5<sup>th</sup> Assessment Report on global warming states that in the 21<sup>st</sup> century, there may be an increase in temperature of the order of ~1.5°C. This transient climate may cause significant impacts or any discrepancies in the water availability of the hydrological unit. This may lead to severe impacts in countries with high population such as India, China, etc., The Remote sensing datasets play an essential role in modelling the climatic changes for a river basin at different spatial and temporal scales. This study aims to propose a conceptual framework for the above-defined problem with emphasising on remote sensing datasets. This framework involves five entities such as the data component, process component,  impact component,  feedback component and, uncertainty component. The framework flow begins with the data component entity that involves two significant inputs, such as the hydro-meteorological data and the land-hydrology data. The essential attributes of the hydro-meteorological data entities are the precipitation, temperature, relative humidity, wind speed and solar radiation. These datasets may be obtained and analysed from empirical or statistical methods, in-situ based or satellite-based methods, respectively. These mathematical models on long-run historical climate data may provide knowledge on climate change detections or its trends. The meteorological data derived from the satellites may have a measurable bias with that of the in situ data. The satellite-based land-hydrology data component involves various attributes such as topography, soil, vegetation, water bodies, other land use / land cover, soil moisture, evapotranspiration. The process component involves complex land-hydrology processes that may be well established and modelled by customizable hydrological models. Here, we may emphasise the use of remote-sensing based model parameter values in the equations either directly or indirectly. Also, the land-atmospheric process component involves various complex processes that may take place in this zone. These processes may be well established and solved by customizable atmospheric weather models. The land components play a significant role in modelling the climate changes, because these land processes may trigger global warming by various anthropogenic agents. The main objective of this framework is to emphasise the climate change impacts using remote sensing. Hence, the impact component entity plays an essential role in this conceptual framework. The climate change impact within a river basin at various spatial and temporal scales are identified using different hydrological responses. The feedback entity is the most sensitive part of this framework, because it may alter the climate forcing either positive or negative. An uncertainty model component handles the uncertainty in the model framework. The highlight of this conceptual framework is to use the remote sensing datasets in climate change studies. The limitations on the correctness of the remote sensing data with the insitu data at every location is not feasible.</p>

scholarly journals Application of swat model in assesment water resources of upper stream of Thi Nai lagoon serving sustainable develoment of Binh Dinh province

2014 ◽  
Vol 17 (2) ◽  
pp. 109-123
Author(s):  
Quan Hong Nguyen ◽  
Thang Toan Mai
Keyword(s):  
Water Resources ◽  
River Basin ◽  
River Flow ◽  
Transport Model ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Water Resources Planning ◽  
Meteorological Input ◽  
Using Data ◽  
Resources Planning

Water resources from Kôn and Hà Thanh river basin, upstream areas of Thi Nai lagoon plays a very essential role on hydrological in economic – social development of Binh Dinh province. Assessment of potential water resources in the region can be servered for water resources planning toward sustainable development. In this paper, the SWAT model was applied in this study to evaluate river flow in the rivers. The simulation data were used with with the length of meteorological input data up to 36 years. The parameters of model were calibrated by SWAT-CUP with Sufi-2 algorithm (Semi Automated Sequential Uncertainty Fitting) using data of Binh Tuong discharge station(1980-1995), that also used to analyze parameter sensitivity. The coefficient of determination (R2), NSE values and PBIAS index for the daily runoff were obtained as 0,54; 0,51 and 15,01 % .The average input flow to Thi Nai lagoon were 105,16 m3/s (from Kon river) and 19,77 m3/s (from Ha Thanh river). The results of this study can be used for others research such as water balance calculation in the river basin or it can be used as inputs of water quality and sediment transport model in Thi Nai lagoon.

scholarly journals Optimal allocation of land and water resources in irrigated agriculture by means of Goal Programming: Application in Loudias River Basin

2013 ◽  
Vol 7 (3) ◽  
pp. 264-273
Keyword(s):  
Water Resources ◽  
Decision Analysis ◽  
River Basin ◽  
Goal Programming ◽  
Agricultural Policy ◽  
Optimal Allocation ◽  
Crop Productivity ◽  
Irrigated Agriculture ◽  
Environmental Goals ◽  
Policy Scenarios

Agriculture is an economic activity that contributes significantly to the gross national product of a country, securing at the same time the viability of the rural sector and the social coherence. On the other hand, it can generate an environmental externality, especially concerning water resources that, in the name of higher crop productivity, are often overexploited or polluted. Most agricultural decision analysis studies are primarily focusing on farmers’ welfare optimization. Therefore, this externality is only examined as a negative environmental effect of different farming and agricultural policy scenarios. However, a proper decision analysis in the field of agricultural policy should be guided by the goal of finding a unique “optimal” solution out of a great number of possible alternatives that arise from a complex integrated socio-economic and environmental system, which incorporates significant conflicted interests. The main objective of this paper is to create, apply and evaluate a model that aims at the simultaneous maximization of farmer’s welfare and the minimization of the consequent environmental burden. More specifically, weighted and lexicographic goal programming techniques are employed. These techniques are implemented on a representative area in the Loudias River Basin in Greece to seek for a compromising solution - in terms of area and water allocation (under different crops) - resulting in figures that will come as close as possible to the decision maker’s economic, social and environmental goals. The information that is incorporated into the selected goals includes farmers’ welfare, characterized by securing income and employment levels, as well as environmental benefits, such as water resources protection from excessive application of fertilizers and from unsustainable use of irrigation water. Several weights or priority levels can be assigned on these goals, according to the intentions of the decision maker, that are likely to differentiate the final allocation of resources. Hence, the analysis is undertaken under different policy scenarios (e.g. environmental friendly, farmers’ friendly and compromising scenarios) and the results are well elucidated. In addition, it is further examined the different final outcome that may arise when the targets of the various economic and environmental goals are relaxed in order to reduce the information bias from the decision maker as well as to better perceive the indirect relationship between some competitive goals.

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