scholarly journals Estimation of Rainfall-Runoff Relationship and Correlation of Runoff with Infiltration Capacity and Temperature Over East Singhbhum District of Jharkhand

In meteorology, Precipitation is any product of the condensation of atmospheric water vapor that falls under the gravity, the rainfall being the principal form of precipitation in India. Rainfall is the most important meteorological parameter for hydrology, as it controls the other processes such as infiltration, runoff, detention storage, and evapotranspiration. When precipitation falls over a catchment area, these processes have to be satisfied before precipitation water becomes runoff. Infiltration is the vertically downward flow of rainfall into ground/underground through percolation inside the soil surface and depends on soil-type, porosity, and permeability. Runoff is the flow of rainwater over the land surface that happens when there is an excess of precipitation over an area. Runoff is produced when the rainwater exceeds the infiltration capacity of the soil. The most important relationships for any watershed are the relationship between rainfall and runoff. This relationship depends on some factors such as characteristics of rainfall, runoff, and infiltration. Though the abovementioned factors have a major impact on the volume of runoff, a consistent correlation between rainfall-runoff enables us to increase more confidence in sufficient time for the formulation of appropriate decision making for the local authority. The present research work was undertaken to analyze the correlation between annual rainfall and annual runoff for the years 1901-2018 over Jamshedpur of East Singhbhum district, Jharkhand. Further in this study, the correlation between infiltration and annual runoff was analyzed over the same area and the same data period. Correlation between temperature and annual runoff was also found. Through the graphical analysis, it was found that the value of annual rainfall and runoff are strongly correlated.As the value of the Pearson correlation coefficient (r) is almost equal to +1 which is a nearly perfect positive correlation, signifies that both variables move in the same direction. It also signifies that the two variables being compared have a perfect positive relationship; that means these two are strongly related. Through the study, it was also found that the infiltration and runoff are largely correlated. There was practically no correlation found between the values of temperature and runoff over the years.

2012 ◽  
Vol 13 (3) ◽  
pp. 932-949 ◽  
Author(s):  
Julie A. Vano ◽  
Tapash Das ◽  
Dennis P. Lettenmaier

Abstract The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at ⅛° latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitation and/or runoff regimes; hence, the highest values are for models biased low in runoff production, and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.


2011 ◽  
Vol 90-93 ◽  
pp. 2578-2582
Author(s):  
Rui Liang ◽  
Qiao Zhu ◽  
Huan Lian Ren ◽  
Hua Jin

Beizhangdian watershed is a typical semi-dry and semi-humid region, where human activities have little effect on the hydrological cycle. Based on a 30-year hydrological observation data, the precipitation, runoff, and rainfall-runoff relationship were researched by the hydrology statistics analysis methods. The results indicated that the inter-annual change of rainfall-runoff of the watershed is remarkable, the annual distribution of rainfall-runoff is extremely uneven, and rainfall-runoff mainly occurred in flood season (June ~ September). There is a good uniformity between the variation tendency of annual rainfall and annual runoff in time and amount, the correlation coefficient of rainfall and runoff is 0.74, the value of the F-test is 4.23.


Author(s):  
M S Boori ◽  
R Paringer ◽  
K Choudhary ◽  
A Kupriyanov

This research work deals with the spatial-temporal characteristics of the relationship between drought events (Standardized Precipitation Index [SPI]), land surface temperature (LSI) and vegetation indexes (VIs) in the spring-summer (May-August) over the European Russia (ER) from 2000 to 2018. We use Terra- MODIS - NDVI and LST product and TRMM for rainfall data. Statistical results indicate that year 2004, 2009 and 2015 were the most significant changing-point in mean annual rainfall values and VIs. Results indicate that vegetation area and VIs variate according to SPI values. Analysis results also indicate that low NDVI values (0.2-0.4) shift in high NDVI values (0.5-0.8) with high SPI values and viceversa, also high LST values associated with low VIs values and vice-versa, with correlation coefficients 0.90, means high-temperature show low vegetation. Correlation analysis of VIs, SPI and LST deficit shows that vegetation is closely related to rainfall and temperature, especially under the dry and wet conditions and indicates that this correlation can use for nearreal-time monitoring of vegetation drought dynamics. All predictions and monitoring using satellite-derived VIs is a low cost and effective means of identifying longer-term changes as opposed to natural inter-annual variability in vegetation growth.


2013 ◽  
Vol 12 (2) ◽  
pp. 119-125

The present study concerns the impact of a change in the rainfall regime on surface and groundwater resources in an experimental watershed. The research is conducted in a gauged mountainous watershed (15.18 km2) that is located on the eastern side of Penteli Mountain, in the prefecture of Attica, Greece and the study period concerns the years from 2003 to 2008. The decrease in the annual rainfall depth during the last two hydrological years 2006-2007, 2007-2008 is 10% and 35%, respectively, in relation to the average of the previous years. In addition, the monthly distribution of rainfall is characterized by a distinct decrease in winter rainfall volume. The field measurements show that this change in rainfall conditions has a direct impact on the surface runoff of the watershed, as well as on the groundwater reserves. The mean annual runoff in the last two hydrological years has decreased by 56% and 75% in relation to the average of the previous years. Moreover, the groundwater level follows a declining trend and has dropped significantly in the last two years.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jacob R. Schaperow ◽  
Dongyue Li ◽  
Steven A. Margulis ◽  
Dennis P. Lettenmaier

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.


2010 ◽  
Vol 11 (1) ◽  
pp. 122-138 ◽  
Author(s):  
Guoxiang Yang ◽  
Laura C. Bowling ◽  
Keith A. Cherkauer ◽  
Bryan C. Pijanowski ◽  
Dev Niyogi

Abstract Impervious surface area (ISA) has different surface characteristics from the natural land cover and has great influence on watershed hydrology. To assess the urbanization effects on streamflow regimes, the authors analyzed the U.S. Geological Survey (USGS) streamflow data of 16 small watersheds in the White River [Indiana (IN)] basin. Correlation between hydrologic metrics (flow distribution, daily variation in streamflow, and frequency of high-flow events) and ISA was investigated by employing the nonparametric Mann–Kendall method. Results derived from the 16 watersheds show that urban intensity has a significant effect on all three hydrologic metrics. The Variable Infiltration Capacity (VIC) model was modified to represent ISA in urbanized basins using a bulk parameterization approach. The model was then applied to the White River basin to investigate the potential ability to simulate the water and energy cycle response to urbanization. Correlation analysis for individual VIC grid cells indicates that the VIC urban model was able to reproduce the slope magnitude and mean value of the USGS streamflow metrics. The urban model also reproduced the urban heat island (UHI) seen in the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature products, especially for the grids encompassing the city of Indianapolis, IN. The difference of the hydrologic metrics obtained from the VIC model with and without urban representation indicates that the streamflow regime in the White River has been modified because of urban development. The observed data, together with model analysis, suggested that 3%–5% ISA in a watershed is the detectable threshold, beyond which urbanization effects start to have a statistically significant influence on streamflow regime.


2021 ◽  
Author(s):  
Dario Ruggiu ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola

<p>The assessment of climate change and land use modifications effects on hydrological cycle is challenging. We propose an approach based on Budyko theory to investigate the relative importance of natural and anthropogenic drivers on water resources availability. As an example of application, the proposed approach is implemented in the island of Sardinia (Italy), which is affected by important processes of both climate and land use modifications. In details, the proposed methodology assumes the Fu’s equation to describe the mechanisms of water partitioning at regional scale and uses the probability distributions of annual runoff (Q) in a closed form. The latter is parametrized by considering simple long-term climatic info (namely first orders statistics of annual rainfall and potential evapotranspiration) and land use properties of basins.</p><p>In order to investigate the possible near future water availability of Sardinia, several climate and land use scenarios have been considered, referring to 2006-2050 and 2051-2100 periods. Climate scenarios have been generated considering fourteen bias corrected outputs of climatic models from EUROCORDEX’s project (RCP 8.5), while three land use scenarios have been created following the last century tendencies.</p><p>Results show that the distribution of annual runoff in Sardinia could be significantly affected by both climate and land use change. The near future distribution of Q generally displayed a decrease in mean and variance compared to the baseline.   </p><p>The reduction of  Q is more critical moving from 2006-2050 to 2051-2100 period, according with climatic trends, namely due to the reduction of annual rainfall and the increase of potential evapotranspiration. The effect of LU change on Q distribution is weaker than the climatic one, but not negligible.</p>


Author(s):  
He Sun ◽  
Fengge Su ◽  
Zhihua He ◽  
Tinghai Ou ◽  
Deliang Chen ◽  
...  

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.


2013 ◽  
Vol 17 (7) ◽  
pp. 2781-2796 ◽  
Author(s):  
S. Shukla ◽  
J. Sheffield ◽  
E. F. Wood ◽  
D. P. Lettenmaier

Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1–6 months) comes from knowledge of initial hydrologic conditions (IHCs) and seasonal climate forecast skill (FS). In this study we quantify the contributions of two primary components of IHCs – soil moisture and snow water content – and FS (of precipitation and temperature) to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two model-based experiments using the variable infiltration capacity (VIC) macroscale hydrology model, one based on ensemble streamflow prediction (ESP) and another based on Reverse-ESP (Rev-ESP), both for a 47 yr re-forecast period (1961–2007). We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings) and estimate the ratio of root mean square error (RMSE) of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude) regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year. Based on our findings, we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.


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