Reliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin,Iran

ABSTRACT

Hydrological models require different inputs for the simulation of processes, among which precipitation is essential. For hydrological simulation, four different precipitation products – Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim); Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) real time (RT); and Precipitation Estimation from Remotely Sensed Information using Arti?cial Neural Networks (PERSIANN) – are compared against ground-based datasets. The variable infiltration capacity (VIC) model was calibrated for the Sefidrood River Basin (SRB), Iran. APHRODITE and ERA-Interim gave better rainfall estimates at daily time scale than other products, with Nash-Sutcliffe efficiency (NSE) values of 0.79 and 0.63, and correlation coefficient (CC) of 0.91 and 0.82, respectively. At the monthly time scale, the CC between all rainfall datasets and ground observations is greater than 0.9, except for TMPA-RT. Hydrological assessment indicates that PERSIANN is the best rainfall dataset for capturing the streamflow and peak flows for the studied area (CC: 0.91, NSE: 0.80).     

Hydrological appraisal of rainfall estimates from radar,satellite, raingauge and satellite–gauge combination on the Qinhuai River Basin,China

ABSTRACT

Multisource rainfall products can be used to overcome the absence of gauged precipitation data for hydrological applications. This study aims to evaluate rainfall estimates from the Chinese S-band weather radar (CINRAD-SA), operational raingauges, multiple satellites (CMORPH, ERA-Interim, GPM, TRMM-3B42RT) and the merged satellite–gauge rainfall products, CMORPH-GC, as inputs to a calibrated probability distribution model (PDM) on the Qinhuai River Basin in Nanjing, China. The Qinhuai is a middle-sized catchment with an area of 799 km². All sources used in this study are capable of recording rainfall at high spatial and temporal resolution (3 h). The discrepancies between satellite and radar data are analysed by statistical comparison with raingauge data. The streamflow simulation results from three flood events suggest that rainfall estimates using CMORPH-GC, TRMM-3B42RT and S-band radar are more accurate than those using the other rainfall sources. These findings indicate the potential to use satellite and radar data as alternatives to raingauge data in hydrological applications for ungauged or poorly gauged basins.     

Hydrological impacts of climate change on rice cultivated riparian wetlands in the Upper Meghna River Basin (Bangladesh and India)

ABSTRACT

Riparian depressional wetlands (haors) in the Upper Meghna River Basin of Bangladesh are invaluable agricultural resources. They are completely flooded between June and November and planted with Boro rice when floodwater recedes in December. However, early harvest period (April/May) floods frequently damage ripening rice. A calibrated/validated Soil and Water Assessment Tool for riparian wetland (SWATrw) model is perturbed with bias free (using an improved quantile mapping approach) climate projections from 17 general circulation models (GCMs) for the period 2031–2050. Projected mean annual rainfall increases (200–500 mm or 7–10%). However, during the harvest period lower rainfall (21–75%) and higher evapotranspiration (1–8%) reduces river discharge (5–18%) and wetland inundation (inundation fraction declines of 0.005–0.14). Flooding risk for Boro rice consequently declines (rationalized flood risk reductions of 0.02–0.12). However, the loss of cultivable land (15.3%) to increases in permanent haor inundation represents a major threat to regional food security.     

Satellite-based rainfall estimation for river flow forecasting in Africa. I: Rainfall estimates and hydrological forecasts

Abstract

Reliable, real-time river flow forecasting in Africa on a time scale of days can provide enormous humanitarian and economic benefits. This study investigates the feasibility of using daily rainfall estimates based on cold cloud duration (CCD) derived from Meteosat thermal infrared imagery as input to a simple rainfall—runoff model and also whether such estimates can be improved by the inclusion of information from numerical weather prediction (NWP) analysis models. The Bakoye catchment in Mali, West Africa has been used as a test area. The data available for the study covered the main months of the rainy season for three years. The rainfall estimates were initially validated against gauge data. Improvements in quality were observed when information relating to African Easterly Wave phase and storm type was included in a multiple linear regression (MR) algorithm. The estimates were also tested by using them as input to a rainfall—runoff model. When contemporaneous calibrations from raingauges were available for calibration, both CCD-only and MR rainfall estimates gave more accurate river flow forecasts than when using raingauge data alone. In the absence of contemporaneous calibrations, the performance was reduced but the MR did better than the CCDonly input in all years. The use of satellite-derived vegetation index did not improve the quality of the river flow forecasts.     

Pre-monsoon rainfall and its variability in Bangladesh: a trend surface analysis / Chute des pluis de la pré-mousson et sa variabilité au Bangladesh: Tendance d'analyse en superficie

Abstract

Bangladesh, with its small but rich agricultural land (total area 9 million ha) and large population (80 million) is faced with an acute food crisis. The economy of Bangladesh is dependent mainly upon agriculture which, in turn, is dependent upon rainfall. An increase in crop acreage and productivity during the pre-monsoon season, March to May, offers a partial solution to the problem. The water available from the rainfall of this season could be utilized through proper planning for better agricultural uses. The present study is an attempt at an inventory of such pre-monsoon rainfall, both monthly and seasonally, and its variability over time and space. The technique employed is that of trend surface mapping.     

The water balance of the Betwa basin,India / Le bilan hydrologique du bassin versant de Betwa en Inde

ABSTRACT

A study of the water balance of a basin in India, where the annual monsoon season of water surplus contrasts with a longer period of deficit, shows that estimates of soil moisture recharge and groundwater recharge may be obtained in these circumstances by comparing seasonal net rainfall with runoff on two assumptions: soil moisture recharge is constant from year to year, and groundwater recharge is proportional to runoff.     

What impact will climate change have on rural groundwater supplies in Africa?

Abstract

One of the key uncertainties surrounding the impacts of climate change in Africa is the effect on the sustainability of rural water supplies. Many of these water supplies abstract from shallow groundwater (<50 m) and are the sole source of safe drinking water for rural populations. Analysis of existing rainfall and recharge studies suggests that climate change is unlikely to lead to widespread catastrophic failure of improved rural groundwater supplies. These require only 10 mm of recharge annually per year to support a hand pump, which should still be achievable for much of the continent, although up to 90 million people may be affected in marginal groundwater recharge areas (200–500 mm annual rainfall). Lessons learnt from groundwater source behaviour during recent droughts, substantiated by groundwater modelling, indicate that increased demand on dispersed water points, as shallow unimproved sources progressively fail, poses a much greater risk of individual source failure than regional resource depletion. Low yielding sources in poor aquifers are most at risk. Predicted increased rainfall intensity may also increase the risk of contamination of very shallow groundwater. Looking to the future, an increase in major groundwater-based irrigation systems, as food prices rise and surface water becomes more unreliable, may threaten long-term sustainability as competition for groundwater increases. To help prepare for increased climate variability, it is essential to understand the balance between water availability, access to water, and use/demand. In practice, this means increasing access to secure domestic water, understanding and mapping renewable and non-renewable groundwater resources, promoting small-scale irrigation and widening the scope of early warning systems and mapping to include access to water.     

Comparison of drought projections using two UK weather generators

Abstract

Possible changes in drought under future climate scenarios may pose unprecedented challenges for water resources, as well as other environmental and societal issues, and need assessment to quantify their associated risk. Two weather generators, based upon (a) the Neyman-Scott Rectangular Pulses (NSRP) model as implemented by the United Kingdom Climate Projections 09 (UKCP09) study, and (b) the generalized linear model (GLM) approach, are used to investigate potential variations in drought conditions for six catchments in the UK under climate projections. The results show that both weather generators provide rainfall simulations having satisfactory monthly statistics. However, the rainfall series from the UKCP09 weather generators lack inter-annual variability, whereas the GLM simulations, which include non-stationary global circulation model (GCM) outputs as driving variables, seem to have a more appropriate representation of the observed drought conditions. For drought projections in the 2080s, the UKCP09 simulations provide repetitive patterns without much temporal variation, similar to the results in the control period. This study suggests that for the drought index considered here (a 3-month drought severity index) the GLM approach appears to be a more appropriate model for drought study on inter-annual scales in comparison with the UKCP09 weather generator.

Editor D. Koutsoyiannis

Citation Chun, K.P., Wheater, H.S., and Onof, C., 2013. Comparison of drought projections using two UK weather generators. Hydrological Sciences Journal, 58 (2), 295–309.     

Spatial and temporal characteristics of rainfall in a data-scarce region: case of Kinshasa and Bas-Congo in Democratic Republic of Congo

ABSTRACT

The aim of the present paper was to improve understanding of the rainfall dynamics in Bas-Congo and Kinshasa provinces, in Democratic Republic of Congo (DRC). The first objective of the study was achieved by analysing the spatial correlations of monthly, seasonal, annual and individual monthly rainfall amounts of Kinshasa and Bas-Congo. The second objective was achieved through investigating and quantifying the temporal trends and their spatial variations. The results demonstrated notably high average inter-station correlation of +0.63 for dry season series, followed by monthly rainfall series with an average inter-station correlation of +0.58. However, there was no station with a stable monthly rainfall regime, i.e. with mean precipitation concentration index lower than 10% (it varies between 14.2 and 21.9%). Moreover, Kinshasa experienced an increase of rainfall with an average annual rate of change of +4.59 mm/year for the period 1961–2006. The results will be helpful for efficient water resources management and for mitigating the adverse impacts of future extreme drought or flood occurrences.

Editor M.C. Acreman Associate editor N. Verhoest     

Temporal and spatial variability of annual and seasonal rainfall over Ethiopia

Abstract

Characterization of the seasonal and inter-annual spatial and temporal variability of rainfall in a changing climate is vital to assess climate-induced changes and suggest adequate future water resources management strategies. Trends in annual, seasonal and maximum 30-day extreme rainfall over Ethiopia are investigated using 0.5° latitude?×?0.5° longitude gridded monthly precipitation data. The spatial coherence of annual rainfall among contiguous rainfall grid points is also assessed for possible spatial similarity across the country. The correlation between temporally coinciding North Atlantic Multidecadal Oscillation (AMO) index and annual rainfall variability is examined to understand the underlying coherence. In total 381 precipitation grid points covering the whole of Ethiopia with five decades (1951–2000) of precipitation data are analysed using the Mann-Kendall test and Moran spatial autocorrelation method. Summer (July–September) seasonal and annual rainfall data exhibit significant decreasing trends in northern, northwestern and western parts of the country, whereas a few grid points in eastern areas show increasing annual rainfall trends. Most other parts of the country exhibit statistically insignificant trends. Regions with high annual and seasonal rainfall distribution exhibit high temporal and spatial correlation indices. Finally, the country is sub-divided into four zones based on annual rainfall similarity. The association of the AMO index with annual rainfall is modestly good for northern and northeastern parts of the country; however, it is weak over the southern region.

Editor Z.W. Kundzewicz; Associate editor S. Uhlenbrook

Citation Wagesho, N., Goel, N.K., and Jain, M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal, 58 (2), 354–373.     

Study on projection of water resources of Dongting Lake catchment based on emission scenarios assumptions

ABSTRACT

With global climate change and impacts of human activity, the water cycle, which has a close relationship with local water resources, has changed rapidly. Based on different greenhouse gas emission scenarios, five relatively independent global climate models are selected from 47 CMIP5 models to simulate future climatic conditions. Data are downscaled to the local projection, with bias neutralized before applying them to the hydrological models, by which availability of future water resources are calculated for the Dongting Lake basin. The results show that the water resources of the Dongting Lake basin are likely to increase in the future, but be distributed more unevenly. All scenarios indicate that water availability will increase during the flood season and decrease during the dry season, with a prominent increase in annual discharge. The scenarios also predict that the greater the greenhouse gas emissions, the more uneven the water distribution becomes. Overall, the water resources of the Dongting Lake catchment show the same increasing and unevenly distributed trend in the future, which could be further accelerated by human activities.

Editor Z.W. Kundzewicz; Associate editor Q. Zhang     

Hydrological simulation of the Betwa River basin (India) using the SWAT model

A seasonal water budget analysis was carried out to quantify various components of the hydrological cycle using the Soil and Water Assessment Tool (SWAT) model for the Betwa River basin (43?500 km²) in central India. The model results were satisfactory in calibration and validation. The seasonal water budget analysis showed that about 90% of annual rainfall and 97% of annual runoff occurred in the monsoon season. A seasonal linear trend analysis was carried out to detect trends in the water balance components of the basin for the period 1973–2001. In the monsoon season, an increasing trend in rainfall and a decreasing trend in ET were observed; this resulted in an increasing trend in groundwater storage and surface runoff. The winter season followed almost the same pattern. A decreasing trend was observed in summer season rainfall. The study evokes the need for conservation structures in the study area to reduce monsoon runoff and conserve it for basin requirements in water-scarce seasons.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR F. Hattermann     

Joint frequency analysis and uncertainty estimation of coupled rainfall–runoff series relying on historical and simulated data

ABSTRACT

Joint frequency analysis and quantile estimation of extreme rainfall and runoff (ERR) are crucial for hydrological engineering designs. The joint quantile estimation of the historical ERR events is subject to uncertainty due to the errors that exist with flow height measurements. This study is motivated by the interest in introducing the advantages of using Hydrologic Simulation Program-Fortran (HSPF) simulations to reduce the uncertainties of the joint ERR quantile estimations in Taleghan watershed. Bivariate ERR quantile estimation was first applied on P_AMS-Q_SIM pairs and the results were compared against the historical rainfall–runoff data (P_AMS-Q_obs). Student’s t and Frank copulas with respectively Gaussian-P3 and Gaussian-LN3 marginal distributions well suited to fit the P_AMS-Q_obs and P_AMS-Q_SIM pairs. Results revealed that confidence regions (CRs) around the p levels become wider for P_AMS-Q_obs compared to P_AMS-Q_SIM, indicating the lower sampling uncertainties of HSPF simulations compared to the historical observations for bivariate ERR frequency analysis.     

Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network,with application to rainfall extremes

The goal of quantile regression is to estimate conditional quantiles for specified values of quantile probability using linear or nonlinear regression equations. These estimates are prone to “quantile crossing”, where regression predictions for different quantile probabilities do not increase as probability increases. In the context of the environmental sciences, this could, for example, lead to estimates of the magnitude of a 10-year return period rainstorm that exceed the 20-year storm, or similar nonphysical results. This problem, as well as the potential for overfitting, is exacerbated for small to moderate sample sizes and for nonlinear quantile regression models. As a remedy, this study introduces a novel nonlinear quantile regression model, the monotone composite quantile regression neural network (MCQRNN), that (1) simultaneously estimates multiple non-crossing, nonlinear conditional quantile functions; (2) allows for optional monotonicity, positivity/non-negativity, and generalized additive model constraints; and (3) can be adapted to estimate standard least-squares regression and non-crossing expectile regression functions. First, the MCQRNN model is evaluated on synthetic data from multiple functions and error distributions using Monte Carlo simulations. MCQRNN outperforms the benchmark models, especially for non-normal error distributions. Next, the MCQRNN model is applied to real-world climate data by estimating rainfall Intensity–Duration–Frequency (IDF) curves at locations in Canada. IDF curves summarize the relationship between the intensity and occurrence frequency of extreme rainfall over storm durations ranging from minutes to a day. Because annual maximum rainfall intensity is a non-negative quantity that should increase monotonically as the occurrence frequency and storm duration decrease, monotonicity and non-negativity constraints are key constraints in IDF curve estimation. In comparison to standard QRNN models, the ability of the MCQRNN model to incorporate these constraints, in addition to non-crossing, leads to more robust and realistic estimates of extreme rainfall.     

Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran

ABSTRACT

The southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.

EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned     

Evaluation of satellite-based rainfall products for hydrological modelling in Morocco

ABSTRACT

Several satellite-based precipitation estimates are becoming available at a global scale, providing new possibilities for water resources modelling, particularly in data-sparse regions and developing countries. This work provides a first validation of five different satellite-based precipitation products (TRMM-3B42 v6 and v7, RFE 2.0, PERSIANN-CDR, CMORPH1.0 version 0.x) in the 1785 km² Makhazine catchment (Morocco). Precipitation products are first compared against ground observations. Ten raingauges and four different interpolation methods (inverse distance, nearest neighbour, ordinary kriging and residual kriging with altitude) were used to compute a set of interpolated precipitation reference fields. Second, a parsimonious conceptual hydrological model is considered, with a simulation approach based on the random generation of model parameters drawn from existing parameter set libraries, to compare the different precipitation inputs. The results indicate that (1) all four interpolation methods, except the nearest neighbour approach, give similar and valid precipitation estimates at the catchment scale; (2) among the different satellite-based precipitation estimates verified, the TRMM-3B42 v7 product is the closest to observed precipitation, and (3) despite poor performance at the daily time step when used in the hydrological model, TRMM-3B42 v7 estimates are found adequate to reproduce monthly dynamics of discharge in the catchment. The results provide valuable perspectives for water resources modelling of data-scarce catchments with satellite-based rainfall data in this region.

Editor M.C. Acreman; Associate editor N. Verhoest     

Impact of climate change on runoff in the upper part of the Euphrates basin

Abstract

Among the processes most affected by global warming are the hydrological cycle and water resources. Regions where the majority of runoff consists of snowmelt are very sensitive to climate change. It is significant to express the relationship between climate change and snow hydrology and it is imperative to perform climate change impact studies on snow hydrology at global and regional scales. Climate change impacts on the mountainous Upper Euphrates Basin were investigated in this paper. First, historical data trend analysis of significant hydro-meteorological data is presented. Available future climate data are then explained, and, finally, future climate data are used in hydrological models, which are calibrated and validated using historical hydro-meteorological data, and future streamflow is projected for the period 2070–2100. The hydrological model outcomes indicate substantial runoff decreases in summer and spring season runoff, which will have significant consequences on water sectors in the Euphrates Basin.

Citation Yilmaz, A.G. & Imteaz, M.A. (2011) Impact of climate change on runoff in the upper part of the Euphrates basin. Hydrol. Sci. J. 56(7), 1265–1279.     

Estimation of rainfall elasticity of streamflow in Australia

Abstract

Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? _P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? _P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.     

Evaluating piezometric trends using the Mann-Kendall test on the alluvial aquifers of the Elqui River basin,Chile

Abstract

Today, more than ever, there is a need to implement robust statistical methods to ensure the proper evaluation of water resources data to support decision makers in water resources planning and management. Graphing or mapping data for visualization is the easiest way to communicate trends, especially to a non-technical audience. This paper describes the use of an approach that combines the Mann-Kendall test, Sen slope test and principal component analysis to detect and map the monthly trends of piezometric time series and their magnitude in the period 1979–2008. The data were obtained in 23 shallow wells in the alluvial aquifers of the Elqui River basin in central Chile, an area characterized by scarce water resources and intense agricultural and mining activities. The results show significant downward trends at the majority of the wells. Because groundwater in these shallow wells is highly dependent on the water in the river and its tributaries, the reasons for these downward trends are mainly related to a decrease of streamflow observed in the Elqui River. The streamflow is derived from mountain snowmelt rather than from rainfall, which showed no flow trend during the same period.     

UTILIZATION OF THE RESULTS FROM REPRESENTATIVE AND EXPERIMENTAL BASINS WITH A VIEW TO THE MANAGEMENT OF WATER RESOURCES / Utilisation des résultats obtenus sur les bassins représentatifs et expérimentaux en vue de l'aménagement des ressources en eau

Abstract

The management of water resources requires knowledge of the spatial and temporal distribution of surface and groundwater resources, and an assessment of the influence of man on the hydrological regime.

For small water courses regional estimates can be made from representative basins which offer guidelines (1) for the computation of mean annual flow and in some cases for the determination of the statistical distribution of the annual flow; (2) for the computation of the 10-year flood maximum discharge and volume.

An example concerning the tropical African Sahel is given. From a general study of the daily precipitation, a simple rainfall/runoff model used on a daily basis and calibrated on data from representative basins, and also the direct comparison of results from 55 representative basins, statistical distribution curves were established for annual runoff based on mean annual precipitation and the geomorphological characteristics of the basins.

Another example concerning tropical Africa west of Congo presents a methodology for the computation of the 10-year flood (maximum discharge and volume).

The systematic study of 60 representative basins makes it possible to plot the runoff coefficient R/P as a function of basin climate, mean slope and soil permeability. Other curves are used to determine the time of rise and the base time of the hydrograph as a function of the basin area and the mean slope.

The experimental basin is a good tool for the assessment of the influence of man on hydrological parameters. An example shows the influence of land use on the regression between annual precipitation and annual runoff.