The European 2015 drought from a hydrological perspective

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G. Laaha

2017-06-01

Full Text Available In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time of the drought of 2015 in terms of both severity (magnitude and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude, pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity

Spatio-Temporal Patterns of the 2010–2015 Extreme Hydrological Drought across the Central Andes, Argentina

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Juan Antonio Rivera

2017-08-01

Full Text Available During the period 2010–2015, the semi-arid Central Andes in Argentina (CAA experienced one of the most severe and long-lasting hydrological droughts on record. Since the snowmelt is the most important source of water, the reduced snowfall over the mountains propagated the drought signal through the streamflows in the adjacent foothills east of the Andes ranges. Motivated by the widespread impacts on the socio-economic activities in the region, this study aims to characterize the recent hydrological drought in terms of streamflow deficits. Based on streamflow data from 20 basins, we used the standardized streamflow index (SSI to characterize hydrological droughts during the period 1971–2016. We found that the regional extent of the 2010–2015 hydrological drought was limited to the basins located north of 38° S, with mean duration of 67 months and maximum drought severity exhibiting a heterogeneous pattern in terms of spatial distribution and time of occurrence. The drought event reached extreme conditions in 14 of the 15 basins in the CAA, being record-breaking drought in six of the basins. This condition was likely driven by a cooling in the tropical Pacific Ocean resembling La Niña conditions, which generated a decrease in snowfall over the Andes due to suppressed frontal activity.

Human water consumption intensifies hydrological drought worldwide

International Nuclear Information System (INIS)

Wada, Yoshihide; Van Beek, Ludovicus P H; Wanders, Niko; Bierkens, Marc F P

2013-01-01

Over the past 50 years, human water use has more than doubled and affected streamflow over various regions of the world. However, it remains unclear to what degree human water consumption intensifies hydrological drought (the occurrence of anomalously low streamflow). Here, we quantify over the period 1960–2010 the impact of human water consumption on the intensity and frequency of hydrological drought worldwide. The results show that human water consumption substantially reduced local and downstream streamflow over Europe, North America and Asia, and subsequently intensified the magnitude of hydrological droughts by 10–500%, occurring during nation- and continent-wide drought events. Also, human water consumption alone increased global drought frequency by 27 (±6)%. The intensification of drought frequency is most severe over Asia (35 ± 7%), but also substantial over North America (25 ± 6%) and Europe (20 ± 5%). Importantly, the severe drought conditions are driven primarily by human water consumption over many parts of these regions. Irrigation is responsible for the intensification of hydrological droughts over the western and central US, southern Europe and Asia, whereas the impact of industrial and households’ consumption on the intensification is considerably larger over the eastern US and western and central Europe. Our findings reveal that human water consumption is one of the more important mechanisms intensifying hydrological drought, and is likely to remain as a major factor affecting drought intensity and frequency in the coming decades. (letter)

Has streamflow changed in the Nordic countries?

Energy Technology Data Exchange (ETDEWEB)

Hisdal, Hege; Holmqvist, Erik; Jonsdottir, Jona Finndis; Jonsson, Pall; Kuusisto, Esko; Lindstroem, Goeran; Roald, Lars A.

2010-01-15

Climate change studies traditionally include elaboration of possible scenarios for the future and attempts to detect a climate change signal in historical data. This study focuses on the latter. A pan-Nordic dataset of more than 160 streamflow records was analysed to detect spatial and temporal changes in streamflow. The Mann-Kendall trend test was applied to study changes in annual and seasonal streamflow as well as floods and droughts for three periods: 1961-2000, 1941-2002 and 1920-2002. The period analysed and the selection of stations influenced the regional patterns found, but the overall picture was that trends towards increased streamflow were dominating for annual values and the winter and spring seasons. Trends in summer flow highly depended on the period analysed whereas no trend was found for the autumn season. A signal towards earlier snowmelt floods was clear and a tendency towards more severe summer droughts was found in southern Norway. A qualitative comparison of the findings to available streamflow scenarios for the region showed that the strongest trends found are coherent with changes expected in the scenario period, for example increased winter discharge and earlier snowmelt floods. However, there are also expected changes that are not reflected in the trends, such as the expected increase in autumn discharge in Norway. It can be concluded that the observed temperature increase has clearly affected the streamflow in the Nordic countries. These changes correspond well with the estimated consequences of a projected temperature increase. The effect of the observed and projected precipitation increase on streamflow is less clear.(Author)

Climate and drought

Science.gov (United States)

McNab, Alan L.

Drought is a complex phenomenon that can be defined from several perspectives [Wilhite and Glantz, 1987]. The common characteristic and central idea of these perspectives is the straightforward notion of a water deficit. Complexity arises because of the need to specify the part of the hydrologic cycle experiencing the deficit and the associated time period. For example, a long-term deficit in deep groundwater storage can occur simultaneously with a short-term surplus of root zone soil water.Figure 1 [Changnon, 1987] illustrates how the definitions of drought are related to specific components of the hydrologic cycle. The dashed lines indicate the delayed translation of two hypothetical precipitation deficits with respect to runoff, soil moisture, streamflow and groundwater. From this perspective, precipitation can be considered as the carrier of the drought signal, and hydrological processes are among the final indicators that reveal the presence of drought [Hare, 1987; Klemes, 1987].

EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

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Norbert A. Agana

2018-02-01

Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

The influence of climate modes on streamflow in the Mid-Atlantic region of the United States

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Justin A. Schulte

2016-03-01

Full Text Available Study region: The Mid-Atlantic region of the United States. Study focus: An understanding of past streamflow variability is necessary for developing future management practices that will help mitigate the impacts of extreme events such as drought or floods on agriculture and other human activities. To better understand mechanisms driving streamflow variability at all timescales, annual to multi-decadal streamflow variability of three major rivers in the Mid-Atlantic region of the United States (the Susquehanna, Delaware, and Hudson Rivers was studied in the context of climate modes using correlation and wavelet analyses. New hydrological insights for the region: Results from the correlation analysis detected statistically significant relationships between climate indices and streamflow that were similar for the three rivers. The results from the wavelet analysis showed that 18- and 26-year periodicities were embedded in the streamflow time series. Decadal variability of streamflow was coherent with the El-Niño Southern Oscillation (SO and the Pacific Decadal Oscillation (PDO. The time series for the PDO and SO indices and precipitation were found to be synchronized to the decadal variability of a global circulation pattern consisting of a Rossby wave train emanating from the North Pacific. The SO explained 37–54% of the 1960s drought, 33–49% of the 1970s pluvial, and 19–50% of the 2000s pluvial in the three river basins. Keywords: Streamflow, Climate, Climate variability, Wavelet analysis, El-Niño-Southern Oscillation, Mid-Atlantic region

Joint pattern of seasonal hydrological droughts and floods alternation in China's Huai River Basin using the multivariate L-moments

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Wu, ShaoFei; Zhang, Xiang; She, DunXian

2017-06-01

Under the current condition of climate change, droughts and floods occur more frequently, and events in which flooding occurs after a prolonged drought or a drought occurs after an extreme flood may have a more severe impact on natural systems and human lives. This challenges the traditional approach wherein droughts and floods are considered separately, which may largely underestimate the risk of the disasters. In our study, the sudden alternation of droughts and flood events (ADFEs) between adjacent seasons is studied using the multivariate L-moments theory and the bivariate copula functions in the Huai River Basin (HRB) of China with monthly streamflow data at 32 hydrological stations from 1956 to 2012. The dry and wet conditions are characterized by the standardized streamflow index (SSI) at a 3-month time scale. The results show that: (1) The summer streamflow makes the largest contribution to the annual streamflow, followed by the autumn streamflow and spring streamflow. (2) The entire study area can be divided into five homogeneous sub-regions using the multivariate regional homogeneity test. The generalized logistic distribution (GLO) and log-normal distribution (LN3) are acceptable to be the optimal marginal distributions under most conditions, and the Frank copula is more appropriate for spring-summer and summer-autumn SSI series. Continuous flood events dominate at most sites both in spring-summer and summer-autumn (with an average frequency of 13.78% and 17.06%, respectively), while continuous drought events come second (with an average frequency of 11.27% and 13.79%, respectively). Moreover, seasonal ADFEs most probably occurred near the mainstream of HRB, and drought and flood events are more likely to occur in summer-autumn than in spring-summer.

Comparison of historical streamflows to 2013 Streamflows in the Williamson, Sprague, and Wood Rivers, Upper Klamath Lake Basin, Oregon

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Hess, Glen W.; Stonewall, Adam J.

2014-01-01

In 2013, the Upper Klamath Lake Basin, Oregon, experienced a dry spring, resulting in an executive order declaring a state of drought emergency in Klamath County. The 2013 drought limited the water supply and led to a near-total cessation of surface-water diversions for irrigation above Upper Klamath Lake once regulation was implemented. These conditions presented a unique opportunity to understand the effects of water right regulation on streamflows. The effects of regulation of diversions were evaluated by comparing measured 2013 streamflow with data from hydrologically similar years. Years with spring streamflow similar to that in 2013 measured at the Sprague River gage at Chiloquin from water years 1973 to 2012 were used to define a Composite Index Year (CIY; with diversions) for comparison to measured 2013 streamflows (no diversions). The best-fit 6 years (1977, 1981, 1990, 1991, 1994, and 2001) were used to determine the CIY. Two streams account for most of the streamflow into Upper Klamath Lake: the Williamson and Wood Rivers. Most streamflow into the lake is from the Williamson River Basin, which includes the Sprague River. Because most of the diversion regulation affecting the streamflow of the Williamson River occurred in the Sprague River Basin, and because of uncertainties about historical flows in a major diversion above the Williamson River gage, streamflow data from the Sprague River were used to estimate the change in streamflow from regulation of diversions for the Williamson River Basin. Changes in streamflow outside of the Sprague River Basin were likely minor relative to total streamflow. The effect of diversion regulation was evaluated using the “Baseflow Method,” which compared 2013 baseflow to baseflow of the CIY. The Baseflow Method reduces the potential effects of summer precipitation events on the calculations. A similar method using streamflow produced similar results, however, despite at least one summer precipitation event. The

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

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Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some

Streamflow response to increasing precipitation extremes altered by forest management

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Charlene N. Kelly; Kevin J. McGuire; Chelcy Ford Miniat; James M. Vose

2016-01-01

Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the...

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

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Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

Tree-ring reconstruction of streamflow in the Snare River Basin, Northwest Territories, Canada

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Martin, J. P.; Pisaric, M. F.

2017-12-01

Drought is a component of many ecosystems in North America causing environmental and socioeconomical impacts. In the ongoing context of climatic and environmental changes, drought-related issues are becoming problematic in northern Canada, which have not been associated with drought-like conditions in the past. Dryer than average conditions threatens the energy security of northern canadian communities, since this region relies on the production of hydroelectricity as an energy source. In the North Slave Region of Northwest Territory (NWT), water levels and streamflows were significantly lower in 2014/2015. The Government of the NWT had to spend nearly $50 million to purchase diesel fuel to generate enough electricity to supplement the reduced power generation of the Snare River hydroelectric system, hence the need to better understand the multi-decadal variability in streamflow. The aims of this presentation are i) to present jack pine and white spruce tree-ring chronologies of Southern NWT; ii) to reconstruct past streamflow of the Snare River Basin; iii) to evaluate the frequency and magnitude of extreme drought conditions, and iv) to identify which large-scale atmospheric or oceanic patterns are teleconnected to regional hydraulic conditions. Preliminary results show that the growth of jack pine and white spruce populations is better correlated with precipitation and temperature, respectively, than hydraulic conditions. Nonetheless, we present a robust streamflow reconstruction of the Snare River that is well correlated with the summer North Atlantic Oscillation (NAO) index, albeit the strength of the correlation is non-stationary. Spectral analysis corroborate the synchronicity between negative NAO conditions and drought conditions. From an operational standpoint, considering that the general occurrence of positive/negative NAO can be predicted, it the hope of the authors that these results can facilitate energetic planning in the Northwest Territories through

Identification of symmetric and asymmetric responses in seasonal streamflow globally to ENSO phase

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Lee, Donghoon; Ward, Philip J.; Block, Paul

2018-04-01

The phase of the El Niño Southern Oscillation (ENSO) has large-ranging effects on streamflow and hydrologic conditions globally. While many studies have evaluated this relationship through correlation analysis between annual streamflow and ENSO indices, an assessment of potential asymmetric relationships between ENSO and streamflow is lacking. Here, we evaluate seasonal variations in streamflow by ENSO phase to identify asymmetric (AR) and symmetric (SR) spatial pattern responses globally and further corroborate with local precipitation and hydrological condition. The AR and SR patterns between seasonal precipitation and streamflow are identified at many locations for the first time. Our results identify strong SR patterns in particular regions including northwestern and southern US, northeastern and southeastern South America, northeastern and southern Africa, southwestern Europe, and central-south Russia. The seasonally lagged anomalous streamflow patterns are also identified and attributed to snowmelt, soil moisture, and/or cumulative hydrological processes across river basins. These findings may be useful in water resources management and natural hazards planning by better characterizing the propensity of flood or drought conditions by ENSO phase.

Streamflow conditions along Soldier Creek, Northeast Kansas

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Juracek, Kyle E.

2017-11-14

The availability of adequate water to meet the present (2017) and future needs of humans, fish, and wildlife is a fundamental issue for the Prairie Band Potawatomi Nation in northeast Kansas. Because Soldier Creek flows through the Prairie Band Potawatomi Nation Reservation, it is an important tribal resource. An understanding of historical Soldier Creek streamflow conditions is required for the effective management of tribal water resources, including drought contingency planning. Historical data for six selected U.S. Geological Survey (USGS) streamgages along Soldier Creek were used in an assessment of streamflow characteristics and trends by Juracek (2017). Streamflow data for the period of record at each streamgage were used to compute annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow. Results of the assessment are summarized in this fact sheet.

Streamflow ratings

Science.gov (United States)

Holmes, Robert R.; Singh, Vijay P.

2016-01-01

Autonomous direct determination of a continuous time series of streamflow is not economically feasible at present (2014). As such, surrogates are used to derive a continuous time series of streamflow. The derivation process entails developing a streamflow rating, which can range from a simple, single-valued relation between stage and streamflow to a fully dynamic one-dimensional model based on hydraulics of the flow.

Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

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J.-P. Vidal

2010-03-01

Full Text Available Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc. on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI – and multiscale hydrological droughts, through the Standardized Flow Index (SFI. Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow. Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990 to short hot and dry periods (2003. Results show that the ranking of drought events depends highly

Examining Severe Drought-Induced Vegetation Change and its Influence on Water Resources

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White, A. B.; Springer, E. P.; Vivoni, E. R.

2007-12-01

A "global-change-type" drought that occurred in the southwestern U.S. from 2000 to 2003, accompanied by increased temperatures and bark beetle infestations, induced large-scale woodland overstory mortality, the consequent redistribution of water, radiation, and nutrients, as well as modification of the ecosystem phenology. Our objectives in this research are to examine these vegetation changes in detail and to determine whether they translated to changes in hydrological processes. We chose the Rio Ojo Caliente, a subbasin of the Rio Grande, as a study site since a significant portion of the woodland ecosystem (piñon-juniper) was affected. Examining a remotely-sensed vegetation index (1-km AVHRR NDVI from 1989 to 2006), there is an increasing trend in the mean NDVI from 1989 to 1998 (pre-drought period), a decreasing trend from 1999 to 2003 (drought period), and a dramatic increasing trend from 2004 to 2006 (post-drought period) in which the mean NDVI rebounds to pre- drought magnitudes. Streamflow records from 1932 to 2006 show the watershed to be primarily spring snowmelt-driven, although monsoonal summer precipitation also plays a significant role. We compare the temporal variability in the streamflow to the NDVI, including the mean, anomalies from the mean, and seasonally- based duration curves, and find significant correlations (correlation coefficient ρ = -0.61) between the streamflow and NDVI at approximately a three-month lag (NDVI lagging streamflow). In analyzing the three phases of the drought, the correlation is slightly stronger during the pre-drought (ρ = -0.64) and drought (ρ = -0.65) periods, yet markedly stronger during the post-drought period (ρ = -0.74). This suggests that the coupling between vegetation water use and streamflow is tighter after the drought. This may be attributable to the reduction in the less-responsive overstory (pinñon mortality) and increase in the more-responsive understory (grasses and shrubs exploiting newly

Climate model assessment of changes in winter-spring streamflow timing over North America

Science.gov (United States)

Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.

2018-01-01

Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

Development of a coastal drought index using salinity data

Science.gov (United States)

Conrads, Paul; Darby, Lisa S.

2017-01-01

A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.

The current California drought through EDDI's eyes: early warning and monitoring of agricultural and hydrologic drought with the new Evaporative Demand Drought Index.

Science.gov (United States)

Hobbins, M.; McEvoy, D.; Huntington, J. L.; Wood, A. W.; Morton, C.; Verdin, J. P.

2015-12-01

We have developed a physically based, multi-scalar drought index—the Evaporative Demand Drought Index (EDDI)—to improve treatment of evaporative dynamics in drought monitoring. Existing popular drought indices—such as the Palmer Drought Severity Index that informs much of the US Drought Monitor (USDM)—have primarily relyied on precipitation and temperature (T) to represent hydroclimatic anomalies, leaving evaporative demand (E0) most often derived from poorly performing T-based parameterizations then used to derive actual evapotranspiration (ET) from LSMs. Instead, EDDI leverages the inter-relations of E0 and ET, measuring E0's physical response to surface drying anomalies due to two distinct land surface/atmosphere interactions: (i) in sustained drought, limited moisture availability forces E0 and ET into a complementary relation, whereby ET declines as E0 increases; and (ii) in "flash" droughts, E0 increases due to increasing advection or radiation. E0's rise in response to both drought types suggests EDDI's robustness as a monitor and leading indicator of drought. To drive EDDI, we use for E0 daily reference ET from the ASCE Standardized Reference ET equation forced by North American Land Data Assimilation System drivers. EDDI is derived by aggregating E0 anomalies from its long-term mean across a period of interest and normalizing them to a Z-score. Positive EDDI indicates drier than normal conditions (and so drought). We use the current historic California drought as a test-case in which to examine EDDI's performance in monitoring agricultural and hydrologic drought. We observe drought development and decompose the behavior of drought's evaporative drivers during in-drought intensification periods and wetting events. EDDI's performance as a drought leading indicator with respect to the USDM is tested in important agricultural regions. Comparing streamflow from several USGS gauges in the Sierra Nevada to EDDI, we find that EDDI tracks most major

Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains

Science.gov (United States)

Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Chen, Yaning; Brenning, Alexander

2018-02-01

Streamflow and snowmelt runoff timing of mountain rivers are susceptible to climate change. Trends and variability in streamflow and snowmelt runoff timing in four mountain basins in the southern Tianshan were analyzed in this study. Streamflow trends were detected by Mann-Kendall tests and changes in snowmelt runoff timing were analyzed based on the winter/spring snowmelt runoff center time (WSCT). Pearson's correlation coefficient was further calculated to analyze the relationships between climate variables, streamflow and WSCT. Annual streamflow increased significantly in past decades in the southern Tianshan, especially in spring and winter months. However, the relations between streamflow and temperature/precipitation depend on the different streamflow generation processes. Annual precipitation plays a vital role in controlling recharge in the Toxkon basin, while the Kaidu and Huangshuigou basins are governed by both precipitation and temperature. Seasonally, temperature has a strong effect on streamflow in autumn and winter, while summer streamflow appears more sensitive to changes in precipitation. However, temperature is the dominant factor for streamflow in the glacierized Kunmalik basin at annual and seasonal scales. An uptrend in streamflow begins in the 1990s at both annual and seasonal scales, which is generally consistent with temperature and precipitation fluctuations. Average WSCT dates in the Kaidu and Huangshuigou basins are earlier than in the Toxkon and Kunmalik basins, and shifted towards earlier dates since the mid-1980s in all the basins. It is plausible that WSCT dates are more sensitive to warmer temperature in spring period compared to precipitation, except for the Huangshuigou basin. Taken together, these findings are useful for applications in flood risk regulation, future hydropower projects and integrated water resources management.

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Science.gov (United States)

Seibert, Mathias; Merz, Bruno; Apel, Heiko

2017-03-01

The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics

Streamflow characteristics and trends along Soldier Creek, Northeast Kansas

Science.gov (United States)

Juracek, Kyle E.

2017-08-16

Historical data for six selected U.S. Geological Survey streamgages along Soldier Creek in northeast Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the Prairie Band Potawatomi Nation for the effective management of tribal water resources, including drought contingency planning. Streamflow data for the period of record at each streamgage were used to assess annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow.Annual mean streamflows along Soldier Creek were characterized by substantial year-to-year variability with no pronounced long-term trends. On average, annual mean base flow accounted for about 20 percent of annual mean streamflow. Mean monthly flows followed a general seasonal pattern that included peak values in spring and low values in winter. Annual peak flows, which were characterized by considerable year-to-year variability, were most likely to occur in May and June and least likely to occur during November through February. With the exception of a weak yet statistically significant increasing trend at the Soldier Creek near Topeka, Kansas, streamgage, there were no pronounced long-term trends in annual peak flows. Annual 1-day, 30-day, and 90-day mean minimum flows were characterized by considerable year-to-year variability with no pronounced long-term trend. During an extreme drought, as was the case in the mid-1950s, there may be zero flow in Soldier Creek continuously for a period of one to several months.

Spatial and Temporal Streamflow Trends in Northern Taiwan

Directory of Open Access Journals (Sweden)

Chen-Feng Yeh

2015-02-01

Full Text Available Streamflow is an important factor in the study of water resource management, floods, and droughts. Dramatic climate change has created extreme rainfall distributions, making the study of streamflow trends and variability even more crucial. In this study, the long-term streamflow data and trends recorded at gauging stations in Northern Taiwan are analyzed using the Mann-Kendall test. The data used for trend analysis are the average annual streamflow, the average seasonal streamflow, and the high and low flows. The slope trend is calculated using the Theil-Sen estimator. Finally, change point analysis is conducted using the Mann-Whitney-Pettit test and the cumulative deviation test to gain further information about the change points and to understand the changes in streamflow before and after the change points. The average annual streamflow of the 12 gauging stations in the study area is analyzed using the Mann-Kendall test. The results show that of the 12 gauging stations, only the Ximen Bridge Station in the Lanyang River basin show a significant downward streamflow trend. Results of the monthly and seasonal average streamflow analysis show that in the spring, 72.2% of the gauging stations showed upward streamflow trends, most of which were located in the Tamsui River and the Touqian River basins. The high and low flow data analysis shows that the Ximen Bridge Station was the only gauging station to feature a significant downward streamflow trend for both high and low flows. This distribution pattern provides valuable information for regional hydrological studies and water management.

Reconstructed streamflow for Citarum River, Java, Indonesia: linkages to tropical climate dynamics

Science.gov (United States)

D'Arrigo, Rosanne; Abram, Nerilie; Ummenhofer, Caroline; Palmer, Jonathan; Mudelsee, Manfred

2011-02-01

The Citarum river basin of western Java, Indonesia, which supplies water to 10 million residents in Jakarta, has become increasingly vulnerable to anthropogenic change. Citarum's streamflow record, only ~45 years in length (1963-present), is too short for understanding the full range of hydrometeorological variability in this important region. Here we present a tree-ring based reconstruction of September-November Citarum streamflow (AD 1759-2006), one of the first such records available for monsoon Asia. Close coupling is observed between decreased tree growth and low streamflow levels, which in turn are associated with drought caused by ENSO warm events in the tropical Pacific and Indian Ocean positive dipole-type variability. Over the full length of record, reconstructed variance was at its weakest during the interval from ~1905-1960, overlapping with a period of unusually-low variability (1920-1960) in the ENSO-Indian Ocean dipole systems. In subsequent decades, increased variance in both the streamflow anomalies and a coral-based SST reconstruction of the Indian Ocean Dipole Mode signal the potential for intensified drought activity and related consequences for water supply and crop productivity in western Java, where much of the country's rice is grown.

Lags in hydrologic recovery following an extreme drought: Assessing the roles of climate and catchment characteristics

Science.gov (United States)

Yang, Yuting; McVicar, Tim R.; Donohue, Randall J.; Zhang, Yongqiang; Roderick, Michael L.; Chiew, Francis H. S.; Zhang, Lu; Zhang, Junlong

2017-06-01

Drought, generally characterized by below-average water supply, propagates through the hydrologic system with consequent ecological and societal impacts. Compared with other drought aspects, the recovery of drought especially in the hydrological components, which directly relates to the recovery of water resources for agricultural, ecological and human needs, is less-understood. Here, taking the Millennium drought in southeast Australia (˜1997-2009) as an illustrating case, we comprehensively examined multiple aspects of the meteorological (i.e., precipitation) and hydrological (i.e., streamflow and base flow) droughts across 130 unimpaired catchments using long-term hydro-meteorological observations. Results show that the duration and intensity of the meteorological drought are both lengthened and amplified in the hydrological drought, suggesting a nonstationarity in the rainfall-runoff relationship during a prolonged drought. Additionally, we find a time lag commonly exists between the end of the meteorological droughts and the end of the hydrological drought, with the recovery of base flow showing a longer lag than the recovery of streamflow. The recovery rate of precipitation after drought was found to be the dominant factor that controls the recovery of hydrological droughts while catchment landscape (i.e., valley bottom flatness) plays an important but secondary role in controlling the lags in the hydrological recovery. Other hydro-climatic factors and catchment properties appear to have only minor influences governing hydrological drought recovery. Our findings highlight a delayed response in the terrestrial components of the hydrological cycle to precipitation after prolonged drought, and provide valuable scientific guidance to water resources management and water security assessment in regions facing future droughts.

Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.: Hydrological Drought in the Anthropocene

Energy Technology Data Exchange (ETDEWEB)

Wan, Wenhua [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; Pacific Northwest National Laboratory, Richland WA USA; Zhao, Jianshi [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; Li, Hong-Yi [Pacific Northwest National Laboratory, Richland WA USA; Now at Department of Land Resources and Environmental Sciences and Institute on Ecosystems, Montana State University, Bozeman MT USA; Mishra, Ashok [Glenn Department of Civil Engineering, Clemson University, Clemson SC USA; Ruby Leung, L. [Pacific Northwest National Laboratory, Richland WA USA; Hejazi, Mohamad [Pacific Northwest National Laboratory, Richland WA USA; Wang, Wei [The Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing China; Lu, Hui [The Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing China; Deng, Zhiqun [Pacific Northwest National Laboratory, Richland WA USA; Demissisie, Yonas [Department of Civil and Environmental Engineering, Washington State University, Pullman WA USA; Wang, Hao [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Hydropower and Water Resources, Beijing China

2017-11-03

Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation, and use the Standardized Streamflow Index (SSI) to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous US in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.

Intensification of hydrological drought due to human activity in the middle reaches of the Yangtze River, China.

Science.gov (United States)

Zhang, Dan; Zhang, Qi; Qiu, Jiaming; Bai, Peng; Liang, Kang; Li, Xianghu

2018-10-01

Hydrological extremes are changing under the impacts of environmental change, i.e., climate variation and human activity, which can substantially influence ecosystems and the living environment of humans in affected region. This study investigates the impacts of environmental change on hydrological drought in the middle reaches of the Yangtze River in China based on hydrological modelling. Change points for streamflow into two major lakes and a reservoir in the study area were detected in the late 1980s using the Mann-Kendall test. Streamflow simulation by a water balance model was performed, and the resulting Kling-Gupta efficiency value was >0.90. Hydrological drought events were identified based on the simulated streamflow under different scenarios. The results show that the hydrological drought occurrence was increased by precipitation, whereas the drought peak value was increased by potential evapotranspiration. The impacts of precipitation and potential evapotranspiration on drought severity and duration varied in the study area. However, hydrological drought was intensified by the influence of human activity, which increased the severity, duration and peak value of droughts. The dominant factor for hydrological drought severity is precipitation, followed by potential evapotranspiration and human activity. The impacts of climate variation and human activity on drought severity are larger than on drought duration. In addition, environmental change is shown to have an "accumulation effect" on hydrological drought, demonstrating that the indirect impacts of environmental change on hydrological drought are much larger than the direct impacts on streamflow. This study improves our understanding of the responses of hydrological extremes to environmental change, which is useful for the management of water resources and the prediction of hydrological disasters. Copyright © 2018 Elsevier B.V. All rights reserved.

Reconstructed streamflow for Citarum River, Java, Indonesia: linkages to tropical climate dynamics

Energy Technology Data Exchange (ETDEWEB)

D' Arrigo, Rosanne [Tree-Ring Laboratory, Lamont-Doherty Earth Observatory, Palisades, NY (United States); Abram, Nerilie [The Australian National University, Research School of Earth Sciences, Canberra (Australia); Natural Environment Research Council, British Antarctic Survey, Cambridge (United Kingdom); Ummenhofer, Caroline [University of New South Wales, Sydney, NSW (Australia); Palmer, Jonathan [Gondwana Tree-Ring Laboratory, Canterbury (New Zealand); Mudelsee, Manfred [Climate Risk Analysis, Hannover (Germany)

2011-02-15

The Citarum river basin of western Java, Indonesia, which supplies water to 10 million residents in Jakarta, has become increasingly vulnerable to anthropogenic change. Citarum's streamflow record, only {proportional_to}45 years in length (1963-present), is too short for understanding the full range of hydrometeorological variability in this important region. Here we present a tree-ring based reconstruction of September-November Citarum streamflow (AD 1759-2006), one of the first such records available for monsoon Asia. Close coupling is observed between decreased tree growth and low streamflow levels, which in turn are associated with drought caused by ENSO warm events in the tropical Pacific and Indian Ocean positive dipole-type variability. Over the full length of record, reconstructed variance was at its weakest during the interval from {proportional_to}1905-1960, overlapping with a period of unusually-low variability (1920-1960) in the ENSO-Indian Ocean dipole systems. In subsequent decades, increased variance in both the streamflow anomalies and a coral-based SST reconstruction of the Indian Ocean Dipole Mode signal the potential for intensified drought activity and related consequences for water supply and crop productivity in western Java, where much of the country's rice is grown. (orig.)

Streamflow timing of mountain rivers in Spain: Recent changes and future projections

Science.gov (United States)

Morán-Tejeda, Enrique; Lorenzo-Lacruz, Jorge; López-Moreno, Juan Ignacio; Rahman, Kazi; Beniston, Martin

2014-09-01

Changes in streamflow timing are studied in 27 mountain rivers in Spain, in the context of climate warming. The studied rivers are characterized by a highflows period in spring due to snowmelt, although differences in the role of snow and consequently in the timing of flows are observed amongst cases. We calculated for every year of the studied period (1976-2008) various hydrological indices that enable locating the timing of spring flows within the annual hydrologic regime, including the day of 75% of mass, and the day of spring maximum. The evolution of these indices was compared with that of seasonal precipitation and temperature, and trends in time were calculated. Results show a general negative trend in the studied indices which indicates that spring peaks due to snowmelt are shifting earlier within the hydrological year. Spring temperatures, which show a significant increasing trend, are the main co-variable responsible for the observed changes in the streamflow timing. In a second set of analyses we performed hydrological simulations with the SWAT model, in order to estimate changes in streamflow timing under projected warming temperatures. Projections show further shifting of spring peak flows along with a more pronounced low water level period in the summer. The simulations also allowed quantifying the role of snowfall-snowmelt on the observed changes in streamflow.

The European 2015 drought from a hydrological perspective

Science.gov (United States)

Laaha, Gregor; Gauster, Tobias; Delus, Claire; Vidal, Jean-Philippe

2016-04-01

The year 2015 was hot and dry in many European countries. A timely assessment of its hydrological impacts constitutes a difficult task, because stream flow records are often not available within 2-3 years after recording. Moreover, monitoring is performed on a national or even provincial basis. There are still major barriers of data access, especially for eastern European countries. Wherever data are available, their compatibility poses a major challenge. In two companion papers we summarize a collaborative initiative of members of UNESCO's FRIEND-Water program to perform a timely Pan-European assessment of the 2015 drought. In this second part we analyse the hydrological perspective based on streamflow observations. We first describe the data access strategy and the assessment method. We than present the results consisting of a range of low flow indices calculated for about 800 gauges across Europe. We compare the characteristics of the 2015 drought with the average, long-term conditions, and with the specific conditions of the 2003 drought, which is often used as a worst-case benchmark to gauge future drought events. Overall, the hydrological 2015 drought is characterised by a much smaller spatial extend than the 2003 drought. Extreme streamflows are observed mainly in a band North of the Alps spanning from E-France to Poland. In terms of flow magnitude, Czech, E-Germany and N-Austria were most affected. In this region the low flows often had return periods of 100 years and more, indicating that the event was much more severe than the 2003 event. In terms of deficit volumes, the centre of the event was more oriented towards S-Germany. Based on a detailed assessment of the spatio-temporal characteristics at various scales, we are able to explain the different behaviour in these regions by diverging wetness preconditions in the catchments. This suggest that the sole knowledge of atmospheric indices is not sufficient to characterise hydrological drought events. We

Long-term variation analysis of a tropical river's annual streamflow regime over a 50-year period

Science.gov (United States)

Seyam, Mohammed; Othman, Faridah

2015-07-01

Studying the long-term changes of streamflow is an important tool for enhancing water resource and river system planning, design, and management. The aim of this work is to identify the long-term variations in annual streamflow regime over a 50-year period from 1961 to 2010 in the Selangor River, which is one of the main tropical rivers in Malaysia. Initially, the data underwent preliminary independence, normality, and homogeneity testing using the Pearson correlation coefficient and Shapiro-Wilk and Pettitt's tests, respectively. The work includes a study and analysis of the changes through nine variables describing the annual streamflow and variations in the yearly duration of high and low streamflows. The analyses were conducted via two time scales: yearly and sub-periodic. The sub-periods were obtained by segmenting the 50 years into seven sub-periods by two techniques, namely the change-point test and direct method. Even though analysis revealed nearly negligible changes in mean annual flow over the study period, the maximum annual flow generally increased while the minimum annual flow significantly decreased with respect to time. It was also observed that the variables describing the dispersion in streamflow continually increased with respect to time. An obvious increase was detected in the yearly duration of danger level of streamflow, a slight increase was noted in the yearly duration of warning and alert levels, and a slight decrease in the yearly duration of low streamflow was found. The perceived changes validate the existence of long-term changes in annual streamflow regime, which increase the probability of floods and droughts occurring in future. In light of the results, attention should be drawn to developing water resource management and flood protection plans in order to avert the harmful effects potentially resulting from the expected changes in annual streamflow regime.

Treating pre-instrumental data as "missing" data: using a tree-ring-based paleoclimate record and imputations to reconstruct streamflow in the Missouri River Basin

Science.gov (United States)

Ho, M. W.; Lall, U.; Cook, E. R.

2015-12-01

Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.

Long-range hydrometeorological ensemble predictions of drought parameters

Science.gov (United States)

Fundel, F.; Jörg-Hess, S.; Zappa, M.

2012-06-01

Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

Groundwater Pumping and Streamflow in the Yuba Basin, Sacramento Valley, California

Science.gov (United States)

Moss, D. R.; Fogg, G. E.; Wallender, W. W.

2011-12-01

Water transfers during drought in California's Sacramento Valley can lead to increased groundwater pumping, and as yet unknown effects on stream baseflow. Two existing groundwater models of the greater Sacramento Valley together with localized, monitoring of groundwater level fluctuations adjacent to the Bear, Feather, and Yuba Rivers, indicate cause and effect relations between the pumping and streamflow. The models are the Central Valley Hydrologic Model (CVHM) developed by the U.S. Geological Survey and C2VSIM developed by Department of Water Resources. Using two models which have similar complexity and data but differing approaches to the agricultural water boundary condition illuminates both the water budget and its uncertainty. Water budget and flux data for localized areas can be obtained from the models allowing for parameters such as precipitation, irrigation recharge, and streamflow to be compared to pumping on different temporal scales. Continuous groundwater level measurements at nested, near-stream piezometers show seasonal variations in streamflow and groundwater levels as well as the timing and magnitude of recharge and pumping. Preliminary results indicate that during years with relatively wet conditions 65 - 70% of the surface recharge for the groundwater system comes from irrigation and precipitation and 30 - 35% comes from streamflow losses. The models further indicate that during years with relatively dry conditions, 55 - 60% of the surface recharge for the groundwater system comes from irrigation and precipitation while 40 - 45% comes from streamflow losses. The models irrigation water demand, surface-water and groundwater supply, and deep percolation are integrated producing values for irrigation pumping. Groundwater extractions during the growing season, approximately between April and October, increase by almost 200%. The effects of increased pumping seasonally are not readily evident in stream stage measurements. However, during dry time

Evidence of increasing drought severity caused by temperature rise in southern Europe

International Nuclear Information System (INIS)

Vicente-Serrano, Sergio M; Lopez-Moreno, Juan-I; Lorenzo-Lacruz, Jorge; García-Ruiz, José M; Azorin-Molina, Cesar; Morán-Tejeda, Enrique; Revuelto, Jesús; Beguería, Santiago; Sanchez-Lorenzo, Arturo; Trigo, Ricardo; Coelho, Fatima; Espejo, Francisco

2014-01-01

We use high quality climate data from ground meteorological stations in the Iberian Peninsula (IP) and robust drought indices to confirm that drought severity has increased in the past five decades, as a consequence of greater atmospheric evaporative demand resulting from temperature rise. Increased drought severity is independent of the model used to quantify the reference evapotranspiration. We have also focused on drought impacts to drought-sensitive systems, such as river discharge, by analyzing streamflow data for 287 rivers in the IP, and found that hydrological drought frequency and severity have also increased in the past five decades in natural, regulated and highly regulated basins. Recent positive trend in the atmospheric water demand has had a direct influence on the temporal evolution of streamflows, clearly identified during the warm season, in which higher evapotranspiration rates are recorded. This pattern of increase in evaporative demand and greater drought severity is probably applicable to other semiarid regions of the world, including other Mediterranean areas, the Sahel, southern Australia and South Africa, and can be expected to increasingly compromise water supplies and cause political, social and economic tensions among regions in the near future. (paper)

Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

Science.gov (United States)

Jaskierniak, D.; Kuczera, G.; Benyon, R.

2016-04-01

A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

Enhancing Access to Drought Information Using the CUAHSI Hydrologic Information System

Science.gov (United States)

Schreuders, K. A.; Tarboton, D. G.; Horsburgh, J. S.; Sen Gupta, A.; Reeder, S.

2011-12-01

The National Drought Information System (NIDIS) Upper Colorado River Basin pilot study is investigating and establishing capabilities for better dissemination of drought information for early warning and management. As part of this study we are using and extending functionality from the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) to provide better access to drought-related data in the Upper Colorado River Basin. The CUAHSI HIS is a federated system for sharing hydrologic data. It is comprised of multiple data servers, referred to as HydroServers, that publish data in a standard XML format called Water Markup Language (WaterML), using web services referred to as WaterOneFlow web services. HydroServers can also publish geospatial data using Open Geospatial Consortium (OGC) web map, feature and coverage services and are capable of hosting web and map applications that combine geospatial datasets with observational data served via web services. HIS also includes a centralized metadata catalog that indexes data from registered HydroServers and a data access client referred to as HydroDesktop. For NIDIS, we have established a HydroServer to publish drought index values as well as the input data used in drought index calculations. Primary input data required for drought index calculation include streamflow, precipitation, reservoir storages, snow water equivalent, and soil moisture. We have developed procedures to redistribute the input data to the time and space scales chosen for drought index calculation, namely half monthly time intervals for HUC 10 subwatersheds. The spatial redistribution approaches used for each input parameter are dependent on the spatial linkages for that parameter, i.e., the redistribution procedure for streamflow is dependent on the upstream/downstream connectivity of the stream network, and the precipitation redistribution procedure is dependent on elevation to account

Spatiotemporal analysis of hydro-meteorological drought in the Johor River Basin, Malaysia

Science.gov (United States)

Tan, Mou Leong; Chua, Vivien P.; Li, Cheng; Brindha, K.

2018-02-01

Assessment of historical hydro-meteorological drought is important to develop a robust drought monitoring and prediction system. This study aims to assess the historical hydro-meteorological drought of the Johor River Basin (JRB) from 1975 to 2010, an important basin for the population of southern Peninsular Malaysia and Singapore. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were selected to represent the meteorological and hydrological droughts, respectively. Four absolute homogeneity tests were used to assess the rainfall data from 20 stations, and two stations were flagged by these tests. Results indicate the SPI duration to be comparatively low (3 months), and drier conditions occur over the upper JRB. The annual SSI had a strong decreasing trend at 95% significance level, showing that human activities such as reservoir construction and agriculture (oil palm) have a major influence on streamflow in the middle and lower basin. In addition, moderate response rate of SSI to SPI was found, indicating that hydrological drought could also have occurred in normal climate condition. Generally, the El Niño-Southern Oscillation and Madden Julian Oscillation have greater impacts on drought events in the basin. Findings of this study could be beneficial for future drought projection and water resources management.

Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

Science.gov (United States)

Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

2017-12-01

Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

The hydroclimatology of UK droughts: evidence from newly recovered and reconstructed datasets from the late 19th century to present

Science.gov (United States)

Smith, K. A.; Hannaford, J.; Bloomfield, J.; McCarthy, M.; Parry, S.; Barker, L. J.; Svensson, C.; Tanguy, M.; Marchant, B.; McKenzie, A.; Legg, T.; Prudhomme, C.

2017-12-01

While the UK is regarded as a wet country, it has periodically suffered from major droughts which have caused serious environmental and societal impacts. Parts of the UK are water stressed and, in a warming world, changes to supply/demand balances could have major implications. There is a pressing need for improved tools for drought risk assessment, which is contingent on a proper understanding of past occurrence of droughts. However, our understanding of hydrological drought occurrence is grounded in the post-1960 period when most UK river flow and groundwater records commenced. As such, water resources planners would benefit from a more thorough assessment of historical drought characteristics and their variability. The multi-disciplinary `Historic Droughts' project thus aims to rigorously characterise droughts in the UK back to the 1890s to inform improved drought management. The foundation of this is a comprehensive characterisation of the hydroclimatology of UK droughts. Here, we present the results of this initiative, based on a hydrological reconstruction campaign of unparalleled scope and detail. Driven by rainfall and potential evapotranspiration data, extended in time using newly recovered observational records, hydro(geo)logical models are used to reconstruct, back to 1890, river flows for >300 catchments across the UK, and groundwater levels from >50 boreholes. The reconstructions are derived within a state-of-the-art modelling framework which allows a comprehensive assessment of uncertainty. A suite of indicators are then applied to these datasets to identify and characterise drought events, integrating precipitation, evapotranspiration, streamflow and groundwater. The work provides new insights into the spatial and temporal dynamics of hitherto poorly quantified late 19th and early 20th century droughts. Similarly, the assessment of temporal variability of drought characteristics benefits from the long timescale of the reconstructions, in turn

Characterizing Drought Risk Management and Assessing the Robustness of Snowpack-based Drought Indicators in the Upper Colorado River Basin.

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Livneh, B.; Badger, A.; Lukas, J.; Dilling, L.; Page, R.

2017-12-01

Drought conditions over the past two decades have arisen during a time of increasing water demands in the Upper Colorado River Basin. The Basin's highly allocated and diverse water systems raise the question of how drought-based information, such as snowpack, streamflow, and reservoir conditions, can be used to inform drought risk management. Like most of the western U.S., snow-water equivalent (SWE) at key dates during the year (e.g., April 1) is routinely used in water resource planning because it is often the highest observed value during the season and it embodies stored water to be released, through melt, during critical periods later in the summer. This presentation will first focus on how water managers on Colorado's Western Slope (a) perceive drought-related risk, (b) use and access drought information, and (c) respond to drought. Preliminary findings will be presented from in-person interviews, document analysis, observations of planning meetings, and other interactions with seven water-management entities across the Western Slope. The second part of the presentation will focus on how the predictive power of snowpack-based drought indicators—identified as the most useful and reliable drought indicator by regional water stakeholders—are expected change in a warmer world, i.e. where expectations are for more rain versus snow, smaller snowpacks, and earlier snowmelt and peak runoff. We will present results from hydrologic simulations using climate projection to examine how a warming climate will affect the robustness of these snowpack-based drought indicators by mid-century.

Climatological aspects of drought in Ohio

International Nuclear Information System (INIS)

Rogers, J.C.

1993-01-01

Precipitation and Palmer hydrological drought index (PHDI) data have been used to identify past occurrences of Ohio drought, to illustrate the temporal variability occurring statewide within dry periods, and to compare some of the key dry spells to those of 1987-88 and 1991-92. Periods of hydrologic drought and low precipitation generally persist for 2 to 5 years and tend to cluster in time, such as occurred from 1930-1966. It is not uncommon for precipitation to return to normal or near normal conditions while short-term drought persists in terms of streamflow, ground water supply, and runoff, as measured by the PHDI. The period April 1930 to March 1931 is the driest on record in Ohio although longer periods of low precipitation have occurred from 1893-1896, 1952-1955, and 1963-1965. The temporal clusters of droughts are separated by prolonged wet periods, including those extending roughly from 1875-1893, 1905-1924, and 1966-1987. Correlations between Ohio monthly precipitation and mean air temperature suggest that drought is linked to unusually high summer temperatures through mechanisms such as increased evapotranspiration, leading to increased fluxes of sensible heat from dry soil surfaces. In winter, warm conditions tend to favor higher precipitation, soil recharge, and runoff. Variations in mean temperature and atmospheric circulation may also be linked to other observed climatic features such as long-term trends in soil-water recharge season (October-March) precipitation

Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

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Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

2015-12-01

A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

The Millennium Drought in southeast Australia (2001-2009): Natural and human causes and implications for water resources, ecosystems, economy, and society

Science.gov (United States)

van Dijk, Albert I. J. M.; Beck, Hylke E.; Crosbie, Russell S.; de Jeu, Richard A. M.; Liu, Yi Y.; Podger, Geoff M.; Timbal, Bertrand; Viney, Neil R.

2013-02-01

The "Millennium Drought" (2001-2009) can be described as the worst drought on record for southeast Australia. Adaptation to future severe droughts requires insight into the drivers of the drought and its impacts. These were analyzed using climate, water, economic, and remote sensing data combined with biophysical modeling. Prevailing El Niño conditions explained about two thirds of rainfall deficit in east Australia. Results for south Australia were inconclusive; a contribution from global climate change remains plausible but unproven. Natural processes changed the timing and magnitude of soil moisture, streamflow, and groundwater deficits by up to several years, and caused the amplification of rainfall declines in streamflow to be greater than in normal dry years. By design, river management avoided impacts on some categories of water users, but did so by exacerbating the impacts on annual irrigation agriculture and, in particular, river ecosystems. Relative rainfall reductions were amplified 1.5-1.7 times in dryland wheat yields, but the impact was offset by steady increases in cropping area and crop water use efficiency (perhaps partly due to CO2 fertilization). Impacts beyond the agricultural sector occurred (e.g., forestry, tourism, utilities) but were often diffuse and not well quantified. Key causative pathways from physical drought to the degradation of ecological, economic, and social health remain poorly understood and quantified. Combined with the multiple dimensions of multiyear droughts and the specter of climate change, this means future droughts may well break records in ever new ways and not necessarily be managed better than past ones.

Summer drought predictability over Europe: empirical versus dynamical forecasts

Science.gov (United States)

Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

2017-08-01

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in Pacific Northwest mountain streams

Science.gov (United States)

Patrick R. Kormos; Charlie Luce; Seth J. Wenger; Wouter R. Berghuijs

2016-01-01

Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important...

Impacts of climate change on hydro-meteorological drought over the Volta Basin, West Africa

Science.gov (United States)

Oguntunde, Philip G.; Abiodun, Babatunde J.; Lischeid, Gunnar

2017-08-01

This study examines the characteristics of drought in the Volta River Basin (VRB), investigates the influence of drought on the streamflow, and projects the impacts of future climate change on the drought. A combination of observation data and regional climate simulations of past and future climates (1970-2013, 2046-2065, and 2081-2100) were analyzed for the study. The Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration (SPEI) were used to characterize drought while the Standardized Runoff Index (SRI) were used to quantify runoff. Results of the study show that the historical pattern of drought is generally consistent with previous studies over the Basin and most part of West Africa. RCA ensemble medians (RMED) give realistic simulations of drought characteristics and area extent over the Basin and the sub-catchments in the past climate. Generally, an increase in drought intensity and spatial extent are projected over VRB for SPEI and SPI, but the magnitude of increase is higher with SPEI than with SPI. Drought frequency (events per decade) may be magnified by a factor of 1.2 (2046-2065) to 1.6 (2081-2100) compared to the present day episodes in the basin. The coupling between streamflow and drought episodes was very strong (P planning how to minimize the negative impacts of future climate change that could have consequences on agriculture, water resources and energy supply.

Dating of streamwater using tritium in a post nuclear bomb pulse world: continuous variation of mean transit time with streamflow

Directory of Open Access Journals (Sweden)

U. Morgenstern

2010-11-01

Full Text Available Tritium measurements of streamwater draining the Toenepi catchment, a small dairy farming area in Waikato, New Zealand, have shown that the mean transit time of the water varies with the flow rate of the stream. Mean transit times through the catchment are 2–5 years during high baseflow conditions in winter, increasing to 30–40 years as baseflow decreases in summer, and then dramatically older water during drought conditions with mean transit time of more than 100 years. Older water is gained in the lower reaches of the stream, compared to younger water in the headwater catchment. The groundwater store supplying baseflow was estimated from the mean transit time and average baseflow to be 15.4 × 10⁶ m³ of water, about 1 m water equivalent over the catchment and 2.3 times total annual streamflow. Nitrate is relatively high at higher flow rates in winter, but is low at times of low flow with old water. This reflects both lower nitrate loading in the catchment several decades ago as compared to current intensive dairy farming, and denitrification processes occurring in the older groundwater. Silica, leached from the aquifer material and accumulating in the water in proportion to contact time, is high at times of low streamflow with old water. There was a good correlation between silica concentration and streamwater age, which potentially allows silica concentrations to be used as a proxy for age when calibrated by tritium measurements. This study shows that tritium dating of stream water is possible with single tritium measurements now that bomb-test tritium has effectively disappeared from hydrological systems in New Zealand, without the need for time-series data.

Sensitivity of streamflow to climate change in California

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Grantham, T.; Carlisle, D.; Wolock, D.; McCabe, G. J.; Wieczorek, M.; Howard, J.

2015-12-01

Trends of decreasing snowpack and increasing risk of drought are looming challenges for California water resource management. Increasing vulnerability of the state's natural water supplies threatens California's social-economic vitality and the health of its freshwater ecosystems. Despite growing awareness of potential climate change impacts, robust management adaptation has been hindered by substantial uncertainty in future climate predictions for the region. Down-scaled global climate model (GCM) projections uniformly suggest future warming of the region, but projections are highly variable with respect to the direction and magnitude of change in regional precipitation. Here we examine the sensitivity of California surface water supplies to climate variation independently of GCMs. We use a statistical approach to construct predictive models of monthly streamflow based on historical climate and river basin features. We then propagate an ensemble of synthetic climate simulations through the models to assess potential streamflow responses to changes in temperature and precipitation in different months and regions of the state. We also consider the range of streamflow change predicted by bias-corrected downscaled GCMs. Our results indicate that the streamflow in the xeric and coastal mountain regions of California is more sensitive to changes in precipitation than temperature, whereas streamflow in the interior mountain region responds strongly to changes in both temperature and precipitation. Mean climate projections for 2025-2075 from GCM ensembles are highly variable, indicating streamflow changes of -50% to +150% relative to baseline (1980-2010) for most months and regions. By quantifying the sensitivity of streamflow to climate change, rather than attempting to predict future hydrologic conditions based on uncertain GCM projections, these results should be more informative to water managers seeking to assess, and potentially reduce, the vulnerability of surface

Global Climate Model Simulated Hydrologic Droughts and Floods in the Nelson-Churchill Watershed

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Vieira, M. J. F.; Stadnyk, T. A.; Koenig, K. A.

2014-12-01

There is uncertainty surrounding the duration, magnitude and frequency of historical hydroclimatic extremes such as hydrologic droughts and floods prior to the observed record. In regions where paleoclimatic studies are less reliable, Global Climate Models (GCMs) can provide useful information about past hydroclimatic conditions. This study evaluates the use of Coupled Model Intercomparison Project 5 (CMIP5) GCMs to enhance the understanding of historical droughts and floods across the Canadian Prairie region in the Nelson-Churchill Watershed (NCW). The NCW is approximately 1.4 million km2 in size and drains into Hudson Bay in Northern Manitoba, Canada. One hundred years of observed hydrologic records show extended dry and wet periods in this region; however paleoclimatic studies suggest that longer, more severe droughts have occurred in the past. In Manitoba, where hydropower is the primary source of electricity, droughts are of particular interest as they are important for future resource planning. Twenty-three GCMs with daily runoff are evaluated using 16 metrics for skill in reproducing historic annual runoff patterns. A common 56-year historic period of 1950-2005 is used for this evaluation to capture wet and dry periods. GCM runoff is then routed at a grid resolution of 0.25° using the WATFLOOD hydrological model storage-routing algorithm to develop streamflow scenarios. Reservoir operation is naturalized and a consistent temperature scenario is used to determine ice-on and ice-off conditions. These streamflow simulations are compared with the historic record to remove bias using quantile mapping of empirical distribution functions. GCM runoff data from pre-industrial and future projection experiments are also bias corrected to obtain extended streamflow simulations. GCM streamflow simulations of more than 650 years include a stationary (pre-industrial) period and future periods forced by radiative forcing scenarios. Quantile mapping adjusts for magnitude

Dendrohydrology and water resources management in south-central Chile: lessons from the Río Imperial streamflow reconstruction

Science.gov (United States)

Fernández, Alfonso; Muñoz, Ariel; González-Reyes, Álvaro; Aguilera-Betti, Isabella; Toledo, Isadora; Puchi, Paulina; Sauchyn, David; Crespo, Sebastián; Frene, Cristian; Mundo, Ignacio; González, Mauro; Vignola, Raffaele

2018-05-01

Streamflow in south-central Chile (SCC, ˜ 37-42° S) is vital for agriculture, forestry production, hydroelectricity, and human consumption. Recent drought episodes have generated hydrological deficits with damaging effects on these activities. This region is projected to undergo major reductions in water availability, concomitant with projected increases in water demand. However, the lack of long-term records hampers the development of accurate estimations of natural variability and trends. In order to provide more information on long-term streamflow variability and trends in SCC, here we report findings of an analysis of instrumental records and a tree-ring reconstruction of the summer streamflow of the Río Imperial ( ˜ 37° 40' S-38° 50' S). This is the first reconstruction in Chile targeted at this season. Results from the instrumental streamflow record ( ˜ 1940 onwards) indicated that the hydrological regime is fundamentally pluvial with a small snowmelt contribution during spring, and evidenced a decreasing trend, both for the summer and the full annual record. The reconstruction showed that streamflow below the average characterized the post-1980 period, with more frequent, but not more intense, drought episodes. We additionally found that the recent positive phase of the Southern Annular Mode has significantly influenced streamflow. These findings agree with previous studies, suggesting a robust regional signal and a shift to a new hydrological scenario. In this paper, we also discuss implications of these results for water managers and stakeholders; we provide rationale and examples that support the need for the incorporation of tree-ring reconstructions into water resources management.

Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

Science.gov (United States)

Wanders, N.; Van Lanen, H. A. J.

2015-03-01

Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

Quantifying human impacts on hydrological drought using a combined modelling approach in a tropical river basin in central Vietnam

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A. B. M. Firoz

2018-01-01

Full Text Available Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB River basin. The Just Another Modelling System (JAMS/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar

Quantifying human impacts on hydrological drought using a combined modelling approach in a tropical river basin in central Vietnam

Science.gov (United States)

Firoz, A. B. M.; Nauditt, Alexandra; Fink, Manfred; Ribbe, Lars

2018-01-01

Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB) River basin. The Just Another Modelling System (JAMS)/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar river basins.

River water quality modelling under drought situations – the Turia River case

Directory of Open Access Journals (Sweden)

J. Paredes-Arquiola

2016-10-01

Full Text Available Drought and water shortage effects are normally exacerbated due to collateral impacts on water quality, since low streamflow affects water quality in rivers and water uses depend on it. One of the most common problems during drought conditions is maintaining a good water quality while securing the water supply to demands. This research analyses the case of the Turia River Water Resource System located in Eastern Spain. Its main water demand comes as urban demand from Valencia City, which intake is located in the final stretch of the river, where streamflow may become very low during droughts. As a result, during drought conditions concentrations of pathogens and other contaminants increase, compromising the water supply to Valencia City. In order to define possible solutions for the above-mentioned problem, we have developed an integrated model for simulating water management and water quality in the Turia River Basin to propose solutions for water quality problems under water scarcity. For this purpose, the Decision Support System Shell AQUATOOL has been used. The results demonstrate the importance of applying environmental flows as a measure of reducing pollutant's concentration depending on the evolution of a drought event and the state of the water resources system.

Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana

Science.gov (United States)

McCarthy, Peter M.

2009-01-01

The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River. Mean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal

Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

Science.gov (United States)

Hadi, Sinan Jasim; Tombul, Mustafa

2018-06-01

Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion

Development of a Coastal Drought Index Using Salinity Data

Science.gov (United States)

Conrads, P. A.; Darby, L. S.

2014-12-01

The freshwater-saltwater interface in surface-water bodies along the coast is an important factor in the ecological and socio-economic dynamics of coastal communities. It influences community composition in freshwater and saltwater ecosystems, determines fisheries spawning habitat, and controls freshwater availability for municipal and industrial water intakes. These dynamics may be affected by coastal drought through changes in Vibrio bacteria impacts on shellfish harvesting and occurrence of wound infection, fish kills, harmful algal blooms, hypoxia, and beach closures. There are many definitions of drought, with most describing a decline in precipitation having negative impacts on water supply and agriculture. Four general types of drought are recognized: hydrological, agricultural, meteorological, and socio-economic. Indices have been developed for these drought types incorporating data such as rainfall, streamflow, soil moisture, groundwater levels, and snow pack. These indices were developed for upland areas and may not be appropriate for characterizing drought in coastal areas. Because of the uniqueness of drought impacts on coastal ecosystems, a need exists to develop a coastal drought index. The availability of real-time and historical salinity datasets provides an opportunity to develop a salinity-based coastal drought index. The challenge of characterizing salinity dynamics in response to drought is excluding responses attributable to occasional saltwater intrusion events. Our approach to develop a coastal drought index modified the Standardized Precipitation Index and applied it to sites in South Carolina and Georgia, USA. Coastal drought indices characterizing 1-, 3-, 6-, 9-, and12-month drought conditions were developed. Evaluation of the coastal drought index indicates that it can be used for different estuary types, for comparison between estuaries, and as an index for wet conditions (high freshwater inflow) in addition to drought conditions.

A near real-time satellite-based global drought climate data record

International Nuclear Information System (INIS)

AghaKouchak, Amir; Nakhjiri, Navid

2012-01-01

Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

Science.gov (United States)

D'Orangeville, Loïc; Maxwell, Justin; Kneeshaw, Daniel; Pederson, Neil; Duchesne, Louis; Logan, Travis; Houle, Daniel; Arseneault, Dominique; Beier, Colin M; Bishop, Daniel A; Druckenbrod, Daniel; Fraver, Shawn; Girard, François; Halman, Joshua; Hansen, Chris; Hart, Justin L; Hartmann, Henrik; Kaye, Margot; Leblanc, David; Manzoni, Stefano; Ouimet, Rock; Rayback, Shelly; Rollinson, Christine R; Phillips, Richard P

2018-02-20

Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ 50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors. © 2018 John Wiley & Sons Ltd.

Uncertainties in Forecasting Streamflow using Entropy Theory

Science.gov (United States)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

Streamflow predictions in Alpine Catchments by using artificial neural networks. Application in the Alto Genil Basin (South Spain)

Science.gov (United States)

Jimeno-Saez, Patricia; Pegalajar-Cuellar, Manuel; Pulido-Velazquez, David

2017-04-01

This study explores techniques of modeling water inflow series, focusing on techniques of short-term steamflow prediction. An appropriate estimation of streamflow in advance is necessary to anticipate measures to mitigate the impacts and risks related to drought conditions. This study analyzes the prediction of future streamflow of nineteen subbasins in the Alto-Genil basin in Granada (Southeast of Spain). Some of these basin streamflow have an important component of snowmelt due to part of the system is located in Sierra Nevada Mountain Range, the highest mountain of continental Spain. Streamflow prediction models have been calibrated using time series of historical natural streamflows. The available streamflow measurements have been downloaded from several public data sources. These original data have been preprocessed to turn them to the original natural regime, removing the anthropic effects. The missing values in the adopted horizon period to calibrate the prediction models have been estimated by using a Temez hydrological balance model, approaching the snowmelt processes with a hybrid degree day method. In the experimentation, ARIMA models are used as baseline method, and recurrent neural networks ELMAN and nonlinear autoregressive neural network (NAR) to test if the prediction accuracy can be improved. After performing the multiple experiments with these models, non-parametric statistical tests are applied to select the best of these techniques. In the experiments carried out with ARIMA, it is concluded that ARIMA models are not adequate in this case study due to the existence of a nonlinear component that cannot be modeled. Secondly, ELMAN and NAR neural networks with multi-start training is performed with each network structure to deal with the local optimum problem, since in neural network training there is a very strong dependence on the initial weights of the network. The obtained results suggest that both neural networks are efficient for the short

Assessment of groundwater response to droughts in a complex runoff-dominated watershed by using an integrated hydrologic model

Science.gov (United States)

Woolfenden, L. R.; Hevesi, J. A.; Nishikawa, T.

2014-12-01

Groundwater is an important component of the water supply, especially during droughts, within the Santa Rosa Plain watershed (SRPW), California, USA. The SRPW is 680 km2 and includes a network of natural and engineered stream channels. Streamflow is strongly seasonal, with high winter flows, predominantly intermittent summer flows, and comparatively rapid response time to larger storms. Groundwater flow is influenced primarily by complex geology, spatial and temporal variation in recharge, and pumping for urban, agricultural, and rural demands. Results from an integrated hydrologic model (GSFLOW) for the SRPW were analyzed to assess the effect of droughts on groundwater resources during water years 1976-2010. Model results indicate that, in general, below-average precipitation during historical drought periods reduced groundwater recharge (focused within stream channels and diffuse outside of channels on alluvial plains), groundwater evapotranspiration (ET), and groundwater discharge to streams (baseflow). In addition, recharge during wet periods was not sufficient to replenish groundwater-storage losses caused by drought and groundwater pumping, resulting in an overall 150 gigaliter loss in groundwater storage for water years 1976-2010. During drought periods, lower groundwater levels from reduced recharge broadly increased the number and length of losing-stream reaches, and seepage losses in streams became a higher percentage of recharge relative to the diffuse recharge outside of stream channels (for example, seepage losses in streams were 36% of recharge in 2006 and 57% at the end of the 2007-09 drought). Reductions in groundwater storage during drought periods resulted in decreased groundwater ET (loss of riparian habitat) and baseflow, especially during the warmer and dryer months (May through September) when groundwater is the dominant component of streamflow.

Seasonal UK Drought Forecasting using Statistical Methods

Science.gov (United States)

Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco

2016-04-01

In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.

Science.gov (United States)

Wan, Wenhua; Zhao, Jianshi; Li, Hong-Yi; Mishra, Ashok; Ruby Leung, L.; Hejazi, Mohamad; Wang, Wei; Lu, Hui; Deng, Zhiqun; Demissisie, Yonas; Wang, Hao

2017-11-01

Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation and use the Standardized Streamflow Index to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous U.S. in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.

Stochastic Drought Risk Analysis and Projection Methods For Thermoelectric Power Systems

Science.gov (United States)

Bekera, Behailu Belamo

the systematic approach can be used for better understanding of pertinent vulnerabilities by providing risk-based information to stakeholders in the power sector. Vulnerabilities as well as our understanding of their extent and likelihood change over time. Keeping up with the changes and making informed decisions demands a time-dependent method that incorporates new evidence into risk assessment framework. This study presents a statistical time-dependent risk analysis approach, which allows for life cycle drought risk assessment of thermoelectric power systems. Also, a Bayesian Belief Network (BBN) extension to the proposed framework is developed. The BBN allows for incorporating new evidence, such as observing power curtailments due to extreme heat or lowflow situations, and updating our knowledge and understanding of the pertinent risk. In sum, the proposed approach can help improve adaptive capacity of the electric power infrastructure, thereby enhancing its resilience to events potentially threatening grid reliability and economic stability. The proposed drought characterization methodology is applied on a daily streamflow series obtained from three United States Geological Survey (USGS) water gauges on the Tennessee River basin. The stochastic water supply risk assessment and projection methods are demonstrated for two power plants on the White River, Indiana: Frank E. Ratts and Petersburg, using water temperature and streamflow time series data obtained from a nearby USGS gauge.

The Global Streamflow Indices and Metadata Archive (GSIM) - Part 2: Quality control, time-series indices and homogeneity assessment

Science.gov (United States)

Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth

2018-04-01

This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM), which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a) describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate), Part 2 introduces a set of quality controlled time-series indices representing (i) the water balance, (ii) the seasonal cycle, (iii) low flows and (iv) floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.

Spatial coherence and large-scale drivers of drought

Science.gov (United States)

Svensson, Cecilia; Hannaford, Jamie

2017-04-01

Drought is a potentially widespread and generally multifaceted natural phenomenon affecting all aspects of the hydrological cycle. It mainly manifests itself at seasonal, or longer, time scales. Here, we use seasonal river flows across the climatologically and topographically diverse UK to investigate the spatial coherence of drought, and explore its oceanic and atmospheric drivers. A better understanding of the spatial characteristics and drivers will improve forecasting and help increase drought preparedness. The location of the UK in the mid-latitude belt of predominantly westerly winds, together with a pronounced topographical divide running roughly from north to south, produce strong windward and leeward effects. Weather fronts associated with storms tracking north-eastward between Scotland and Iceland typically lead to abundant precipitation in the mountainous north and west, while the south and east remain drier. In contrast, prolonged precipitation in eastern Britain tends to be associated with storms on a more southerly track, producing precipitation in onshore winds on the northern side of depressions. Persistence in the preferred storm tracks can therefore result in periods of wet/dry conditions across two main regions of the UK, a mountainous northwest region exposed to westerly winds and a more sheltered, lowland southeast region. This is reflected in cluster analyses of monthly river flow anomalies. A further division into three clusters separates out a region of highly permeable, slowly responding, catchments in the southeast. An expectation that the preferred storm tracks over seasonal time scales can be captured by atmospheric airflow indices, which in turn may be related to oceanic conditions, suggests that statistical methods may be used to describe the relationships between UK regional streamflows, and oceanic and atmospheric drivers. Such relationships may be concurrent or lagged, and the longer response time of the group of permeable

Skilful seasonal forecasts of streamflow over Europe?

Science.gov (United States)

Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian

2018-04-01

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate

High-Resolution Near Real-Time Drought Monitoring in South Asia

Science.gov (United States)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

Science.gov (United States)

Park, D. H.; Lee, J. Y.; Lee, J. H.; KIm, T. W.

2017-12-01

Drought monitoring has already been extensively studied due to the widespread impacts and complex causes of drought. The most important component of drought monitoring is to estimate the characteristics and extent of drought by quantitatively measuring the characteristics of drought. Drought assessment considering different aspects of the complicated drought condition and uncertainty of drought index is great significance in accurate drought monitoring. This study used the dynamic Naïve Bayesian Classifier (DNBC) which is an extension of the Hidden Markov Model (HMM), to model and classify drought by using various drought indices for integrated drought assessment. To provide a stable model for combined use of multiple drought indices, this study employed the DNBC to perform multi-index drought assessment by aggregating the effect of different type of drought and considering the inherent uncertainty. Drought classification was performed by the DNBC using several drought indices: Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Normalized Vegetation Supply Water Index (NVSWI)) that reflect meteorological, hydrological, and agricultural drought characteristics. Overall results showed that in comparison unidirectional (SPI, SDI, and NVSWI) or multivariate (Composite Drought Index, CDI) drought assessment, the proposed DNBC was able to synthetically classify of drought considering uncertainty. Model provided method for comprehensive drought assessment with combined use of different drought indices.

Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales

Science.gov (United States)

Villarini, G.; Slater, L. J.; Salvi, K. A.

2017-12-01

Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.

Understanding uncertainties in future Colorado River streamflow

Science.gov (United States)

Julie A. Vano,; Bradley Udall,; Cayan, Daniel; Jonathan T Overpeck,; Brekke, Levi D.; Das, Tapash; Hartmann, Holly C.; Hidalgo, Hugo G.; Hoerling, Martin P; McCabe, Gregory J.; Morino, Kiyomi; Webb, Robert S.; Werner, Kevin; Lettenmaier, Dennis P.

2014-01-01

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.

The Global Streamflow Indices and Metadata Archive (GSIM – Part 2: Quality control, time-series indices and homogeneity assessment

Directory of Open Access Journals (Sweden)

L. Gudmundsson

2018-04-01

Full Text Available This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM, which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate, Part 2 introduces a set of quality controlled time-series indices representing (i the water balance, (ii the seasonal cycle, (iii low flows and (iv floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

Directory of Open Access Journals (Sweden)

Zheng Li

2015-07-01

Full Text Available Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI. We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI, from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months. When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October. The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

Low Streamflow Forcasting using Minimum Relative Entropy

Science.gov (United States)

Cui, H.; Singh, V. P.

2013-12-01

Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

NARCIS (Netherlands)

Wanders, N.; Van Lanen, H. A J

2015-01-01

Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study

2003 hydrological drought - natural disaster

International Nuclear Information System (INIS)

Trninic, Dusan; Bosnjak, Tomislava

2004-01-01

An exceptionally dry and warm period from February to early October 2003 resulted in hydrological drought with attributes of a natural disaster in most of the Croatian regions. The paper presents hydrological analysis of the Sava River near Zupanja for the period 1945-2003 (N=59 years). In defining maximum annual volumes of isolated waves below the reference discharges, the following reference discharges were used:Q 30,95% = 202m 3 s -1 - minimum mean 30-day discharge, 95 % probability, Q 30,80% = 254m 3 s -1 - minimum mean 30-day discharge, 80 % probability, Q 95% = 297m 3 s -1 - (H = -17cm minimum navigation level = 95 % of water level duration from average duration curve). The analysis results have shown that the hydrological drought recorded during the current year belongs to the most thoroughly studied droughts in 59 years. For example, hydrological analysis of the reference discharge of 297m 3 s -1 has shown that this year drought comes second, immediately after the driest year 1946. However, this year hydrological drought hit the record duration of 103 days, unlike the one from 1946, which lasted 98 days. It is interesting that the hydrological droughts affect the Sava River usually in autumn and summer, rarely in winter, and it has never been recorded in spring (referring to the analysed 1945-2003 period). In conclusion, some recommendations are given for increase in low streamflows and on possible impacts of climate changes on these flows.(Author)

Estimating ice-affected streamflow by extended Kalman filtering

Science.gov (United States)

Holtschlag, D.J.; Grewal, M.S.

1998-01-01

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

On the use of Standardized Drought Indices under decadal climate variability: Critical assessment and drought policy implications

Science.gov (United States)

Núñez, J.; Rivera, D.; Oyarzún, R.; Arumí, J. L.

2014-09-01

Since the recent High Level Meeting on National Drought Policy held in Geneva in 2013, a greater concern about the creation and adaptation of national drought monitoring systems is expected. Consequently, backed by international recommendations, the use of Standardized Drought Indices (SDI), such as the Standardized Precipitation Index (SPI), as an operational basis of drought monitoring systems has been increasing in many parts of the world. Recommendations for the use of the SPI, and consequently, those indices that share its properties, do not take into account the limitations that this type of index can exhibit under the influence of multidecadal climate variability. These limitations are fundamentally related to the lack of consistency among the operational definition expressed by this type of index, the conceptual definition with which it is associated and the political definition it supports. Furthermore, the limitations found are not overcome by the recommendations for their application. This conclusion is supported by the long-term study of the Standardized Streamflow Index (SSI) in the arid north-central region of Chile, under the influence of multidecadal climate variability. The implications of the findings of the study are discussed with regard to their link to aspects of drought policy in the cases of Australia, the United States and Chile.

An extended multivariate framework for drought monitoring in Mexico

Science.gov (United States)

Real-Rangel, Roberto; Pedrozo-Acuña, Adrián; Breña-Naranjo, Agustín; Alcocer-Yamanaka, Víctor

2017-04-01

Around the world, monitoring natural hazards, such as droughts, represents a critical task in risk assessment and management plans. A reliable drought monitoring system allows to identify regions affected by these phenomena so that early response measures can be implemented. In Mexico, this activity is performed using Mexico's Drought Monitor, which is based on a similar methodology as the United States Drought Monitor and the North American Drought Monitor. The main feature of these monitoring systems is the combination of ground-based and remote sensing observations that is ultimately validated by local experts. However, in Mexico in situ records of variables such as precipitation and streamflow are often scarce, or even null, in many regions of the country. Another issue that adds uncertainty in drought monitoring is the arbitrary weight given to each analyzed variable. This study aims at providing an operational framework for drought monitoring in Mexico, based on univariate and multivariate nonparametric standardized indexes proposed in recent studies. Furthermore, the framework has been extended by taking into account the Enhanced Vegetation Index (EVI) for the drought severity assessment. The analyzed variables used for computing the drought indexes are mainly derived from remote sensing (MODIS) and land surface models datasets (NASA MERRA-2). A qualitative evaluation of the results shows that the indexes used are capable of adequately describes the intensity and spatial distribution of past drought documented events.

Increasing influence of air temperature on upper Colorado River streamflow

Science.gov (United States)

Woodhouse, Connie A.; Pederson, Gregory T.; Morino, Kiyomi; McAfee, Stephanie A.; McCabe, Gregory J.

2016-01-01

This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.

Time-dependent leaf proteome alterations of Brachypodium distachyon in response to drought stress.

Science.gov (United States)

Tatli, Ozge; Sogutmaz Ozdemir, Bahar; Dinler Doganay, Gizem

2017-08-01

For the first time, a comprehensive proteome analysis was conducted on Brachypodium leaves under drought stress. Gradual changes in response to drought stress were monitored. Drought is one of the major stress factors that dramatically affect the agricultural productivity worldwide. Improving the yield under drought is an urgent challenge in agriculture. Brachypodium distachyon is a model species for monocot plants such as wheat, barley and several potential biofuel grasses. In the current study, a comprehensive proteome analysis was conducted on Brachypodium leaves under different levels of drought application. To screen gradual changes upon drought, Brachypodium leaves subjected to drought for 4, 8 and 12 days were collected for each treatment day and relative water content of the leaves was measured for each time point. Cellular responses of Brachypodium were investigated through a proteomic approach involving two dimensional difference gel electrophoresis (2D-DIGE) and mass spectrometry (MS). Among 497 distinct spots in Brachypodium protein repertoire, a total of 13 differentially expressed proteins (DEPs) were identified as responsive to drought by mass spectrometry and classified according to their functions using bioinformatics tools. The biological functions of DEPs included roles in photosynthesis, protein folding, antioxidant mechanism and metabolic processes, which responded differentially at each time point of drought treatment. To examine further transcriptional expression of the genes that code identified protein, quantitative real time PCR (qRT-PCR) was performed. Identified proteins will contribute to the studies involving development of drought-resistant crop species and lead to the delineation of molecular mechanisms in drought response.

Streamflow depletion by wells--Understanding and managing the effects of groundwater pumping on streamflow

Science.gov (United States)

Barlow, Paul M.; Leake, Stanley A.

2012-11-02

Groundwater is an important source of water for many human needs, including public supply, agriculture, and industry. With the development of any natural resource, however, adverse consequences may be associated with its use. One of the primary concerns related to the development of groundwater resources is the effect of groundwater pumping on streamflow. Groundwater and surface-water systems are connected, and groundwater discharge is often a substantial component of the total flow of a stream. Groundwater pumping reduces the amount of groundwater that flows to streams and, in some cases, can draw streamflow into the underlying groundwater system. Streamflow reductions (or depletions) caused by pumping have become an important water-resource management issue because of the negative impacts that reduced flows can have on aquatic ecosystems, the availability of surface water, and the quality and aesthetic value of streams and rivers. Scientific research over the past seven decades has made important contributions to the basic understanding of the processes and factors that affect streamflow depletion by wells. Moreover, advances in methods for simulating groundwater systems with computer models provide powerful tools for estimating the rates, locations, and timing of streamflow depletion in response to groundwater pumping and for evaluating alternative approaches for managing streamflow depletion. The primary objective of this report is to summarize these scientific insights and to describe the various field methods and modeling approaches that can be used to understand and manage streamflow depletion. A secondary objective is to highlight several misconceptions concerning streamflow depletion and to explain why these misconceptions are incorrect.

Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

Science.gov (United States)

Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-02-24

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water

Analysis of Droughts of Northwest of Iran Using the Reconnaissance Drought Index

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behrouz hosseini

2016-02-01

Full Text Available Introduction: Drought is a creeping natural phenomenon, which can occur in any region. Such phenomenon not only affects the region subjected to drought, but its adverse effects can also be extended to other adjacent regions. This phenomenon mainly starts with water deficiency (say less than long- term mean of variable under study such as rainfall, streamflow, groundwater level or soil moisture and progress in time. This period can be ended by increasing the rainfall and reaching the mean level. Even after the ending of a drought period, its adverse effects can be continued for several months. Although, it is not possible (at least at this time to prevent the occurrence of drought in a given region, it is not impossible to alleviate the drought consequences by scientific water management. Such a management should be employed before drought initiation as well as during it and continue on even after the end of the drought period. The frequency of the main drought characteristics is a major concern of this study. The Northwest of Iran recently encountered severe and prolonged droughts, such that a major portion of the Urmia Lake surface disappeared during the last drought in recent years. In order to study drought characteristics, we used the Reconnaissance Drought Index (RDI. This index is based on annual rainfall and potential reference crop evapotranspiration (abbreviated by PET here. This study employed the Monte Carlo simulation technique for synthetic data generation for analysis. Materials and Methods: The information from the 17 synoptic weather stations located in the North-west of Iran was used for drought analysis. Data was gathered from the Islamic Republic of Iran’s Meteorological Organization (IRIMO. In the first stage of research, the ratio of long term mean annual precipitation to evapotranspiration was calculated for each of the stations. For this purpose, the Penman-Montheis (FAO 56 method was selected for PET estimation. In the

Regional applicability of seven meteorological drought indices in China

Institute of Scientific and Technical Information of China (English)

YANG Qing; LI MingXing; ZHENG ZiYan; MA ZhuGuo

2017-01-01

The definition of a drought index is the foundation of drought research.However,because of the complexity of drought,there is no a unified drought index appropriate for different drought types and objects at the same time.Therefore,it is crucial to determine the regional applicability of various drought indices.Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment,and the observed soil moisture and streamflow in China,we evaluated the regional applicability of seven meteorological drought indices:the Palmer Drought Severity Index(PDSI),modified PDSI(PDSI_CN) based on observations in China,self-calibrating PDSI(scPDSI),Surface Wetness Index(SWI),Standardized Precipitation Index(SPI),Standardized Precipitation Evapotranspiration Index(SPEI),and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing(CLM3.5/ObsFC).The results showed that the scPDSI is most appropriate for China.However,it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN;thus,the classification of dry and wet conditions should be adjusted accordingly.Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters.The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas.This is because contributions of temperature variation to drought are neglected in the SPI,but overestimated in the SPEI,when potential evapotranspiration is estimated by the Thornthwaite method in these areas.Consequently,the SPI and SPEI tend to induce wetter and drier results,respectively.The CLM3.5/ObsFC is suitable for China before 2000,but not for arid and semiarid areas after 2000.Consistent with other drought indices,the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations.Although the long-term trends of drought areas in China detected by these seven

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

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Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

A national perspective on paleoclimate streamflow and water storage infrastructure in the conterminous United States

Science.gov (United States)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward

2017-04-01

Large-scale water storage infrastructure in the Conterminous United States (CONUS) provides a means of regulating the temporal variability in water supply with storage capacities ranging from seasonal storage in the wetter east to multi-annual and decadal-scale storage in the drier west. Regional differences in water availability across the CONUS provides opportunities for optimizing water dependent economic activities, such as food and energy production, through storage and transportation. However, the ability to sufficiently regulate water supplies into the future is compromised by inadequate monitoring of non-federally-owned dams that make up around 97% of all dams. Furthermore, many of these dams are reaching or have exceeded their economic design life. Understanding the role of dams in the current and future landscape of water requirements in the CONUS is needed to prioritize dam safety remediation or identify where redundant dams may be removed. A national water assessment and planning process is needed for addressing water requirements, accounting for regional differences in water supply and demand, and the role of dams in such a landscape. Most dams in the CONUS were designed without knowledge of devastating floods and prolonged droughts detected in multi-centennial paleoclimate records, consideration of projected climate change, nor consideration of optimal operation across large-scale regions. As a step towards informing water supply across the CONUS we present a paleoclimate reconstruction of annual streamflow across the CONUS over the past 555 years using a spatially and temporally complete paleoclimate record of summer drought across the CONUS targeting a set of US Geological Survey streamflow sites. The spatial and temporal structures of national streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s

Assessing and mapping drought hazard in Africa and South-Central America with a Meteorological Drought Severity Index

Science.gov (United States)

Carrao, Hugo; Barbosa, Paulo; Vogt, Jürgen

2015-04-01

Drought is a recurring extreme climate event characterized by a temporary deficit of precipitation, soil moisture, streamflow, or any combination of the three taking place at the same time. The immediate consequences of short-term (i.e. a few weeks duration) droughts are, for example, a fall in crop production, poor pasture growth and a decline in fodder supplies from crop residues, whereas prolonged water shortages (e.g. of several months or years duration) may, amongst others, lead to a reduction in hydro-electrical power production and an increase of forest fires. As a result, comprehensive drought risk management is nowadays critical for many regions in the world. Examples are many African and South-and Central American countries that strongly depend on rain-fed agriculture for economic development with hydroelectricity and biomass as main sources of energy. Drought risk is the probability of harmful consequences, or expected losses resulting from interactions between drought hazard, i.e. the physical nature of droughts, and the degree to which a population or activity is vulnerable to its effects. As vulnerability to drought is increasing globally and certain tasks, such as distributive policies (e.g. relief aid, regulatory exemptions, or preparedness investments), require information on drought severity that is comparable across different climatic regions, greater attention has recently been directed to the development of methods for a standardized quantification of drought hazard. In this study we, therefore, concentrate on a methodology for assessing the severity of historical droughts and on mapping the frequency of their occurrence. To achieve these goals, we use a new Meteorological Drought Severity Index (MDSI). The motivation is twofold: 1) the observation that primitive indices of drought severity directly measure local precipitation shortages and cannot be compared geographically; and that 2) standardized indices of drought do not take into account

Benchmarking ensemble streamflow prediction skill in the UK

Science.gov (United States)

Harrigan, Shaun; Prudhomme, Christel; Parry, Simon; Smith, Katie; Tanguy, Maliko

2018-03-01

Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decision-making in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble streamflow prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions, instead using initial hydrologic conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce a 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1 day to 12 months initialized at the first of each month over a 50-year hindcast period from 1965 to 2015. Results showed ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. UK-wide mean ESP skill decayed exponentially as a function of lead time with continuous ranked probability skill scores across the year of 0.75, 0.20, and 0.11 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialization months. For lead times up to 1 month, ESP skill was higher than average when initialized in summer and lower in winter months, whereas for longer seasonal and annual lead times skill was higher when initialized in autumn and winter months and lowest in spring. ESP was most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located

Seasonal Patterns of Gastrointestinal Illness and Streamflow along the Ohio River

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Elena N. Naumova

2012-05-01

Full Text Available Waterborne gastrointestinal (GI illnesses demonstrate seasonal increases associated with water quality and meteorological characteristics. However, few studies have been conducted on the association of hydrological parameters, such as streamflow, and seasonality of GI illnesses. Streamflow is correlated with biological contamination and can be used as proxy for drinking water contamination. We compare seasonal patterns of GI illnesses in the elderly (65 years and older along the Ohio River for a 14-year period (1991–2004 to seasonal patterns of streamflow. Focusing on six counties in close proximity to the river, we compiled weekly time series of hospitalizations for GI illnesses and streamflow data. Seasonal patterns were explored using Poisson annual harmonic regression with and without adjustment for streamflow. GI illnesses demonstrated significant seasonal patterns with peak timing preceding peak timing of streamflow for all six counties. Seasonal patterns of illness remain consistent after adjusting for streamflow. This study found that the time of peak GI illness precedes the peak of streamflow, suggesting either an indirect relationship or a more direct path whereby pathogens enter water supplies prior to the peak in streamflow. Such findings call for interdisciplinary research to better understand associations among streamflow, pathogen loading, and rates of gastrointestinal illnesses.

Simulation of groundwater conditions and streamflow depletion to evaluate water availability in a Freeport, Maine, watershed

Science.gov (United States)

Nielsen, Martha G.; Locke, Daniel B.

2012-01-01

, the public-supply withdrawals (105.5 million gallons per year (Mgal/yr)) were much greater than those for any other category, being almost 7 times greater than all domestic well withdrawals (15.3 Mgal/yr). Industrial withdrawals in the study area (2.0 Mgal/yr) are mostly by a company that withdraws from an aquifer at the edge of the Merrill Brook watershed. Commercial withdrawals are very small (1.0 Mgal/yr), and no irrigation or other agricultural withdrawals were identified in this study area. A three-dimensional, steady-state groundwater-flow model was developed to evaluate stream-aquifer interactions and streamflow depletion from pumping, to help refine the conceptual model, and to predict changes in streamflow resulting from changes in pumping and recharge. Groundwater levels and flow in the Freeport aquifer study area were simulated with the three-dimensional, finite-difference groundwater-flow modeling code, MODFLOW-2005. Study area hydrology was simulated with a 3-layer model, under steady-state conditions. The groundwater model was used to evaluate changes that could occur in the water budgets of three parts of the local hydrologic system (the Harvey Brook watershed, the Merrill Brook watershed, and the buried aquifer from which pumping occurs) under several different climatic and pumping scenarios. The scenarios were (1) no pumping well withdrawals; (2) current (2009) pumping, but simulated drought conditions (20-percent reduction in recharge); (3) current (2009) recharge, but a 50-percent increase in pumping well withdrawals for public supply; and (4) drought conditions and increased pumping combined. In simulated drought situations, the overall recharge to the buried valley is about 15 percent less and the total amount of streamflow in the model area is reduced by about 19 percent. Without pumping, infiltration to the buried valley aquifer around the confining unit decreased by a small amount (0.05 million gallons per day (Mgal/d)), and discharge to the

Testing the sensitivity of trade linkages in Europe to compound drought events

Science.gov (United States)

Veldkamp, Ted; Koks, Elco; Thissen, Mark; Wahl, Thomas; Haigh, Ivan; Muis, Sanne; Ward, Philip

2017-04-01

Droughts can be defined as spatially extensive events that are characterized by temporal deficits in precipitation, soil moisture or streamflow, and have the potential to cause large direct and indirect economic losses. Many European countries face drought as an economically important hazard, with agriculture, livestock, forestry, energy, industry, and water sectors particularly at risk, causing economic losses of 139 billion US over the past 30 years. Apart from these direct impacts, business production and the flow of goods and services can be affected indirectly by droughts. With consequences that can propagate through the economic system affecting regions not directly hit by the drought event itself, or in time-periods long after the original drought event occurred. In this study, we evaluate the sensitivity of existing trade linkages between the different NUTS-2 regions in Europe to the coupled occurrence of hydro-meteorological drought events, and their associated production losses. Using a multi-regional supply-use model for Europe, we have, on a product level, insight in the existing trade linkages between NUTS-2 regions. Using this information in combination with historical drought data, we assessed and identified for a selection of water related products: 1) the dependency-structures of the NUTS-2 regions within Europe for the import and export of products (and therein water); 2) the coupled nature of drought events occurring in regions that are linked via these trade-patterns; 3) the probability of not meeting demands (on a product level) due to drought events and the associated (indirect economic) impacts; and 4) regions that lose or benefit from their selection of trade-partners given the coupled nature of drought events, as well as the net effects for Europe as a whole.

Dynamics of meteorological and hydrological droughts in the Neman river basin

International Nuclear Information System (INIS)

Rimkus, Egidijus; Stonevičius, Edvinas; Kažys, Justas; Valiuškevičius, Gintaras; Korneev, Vladimir; Pakhomau, Aliaksandr

2013-01-01

The analysis of drought dynamics in the Neman river basin allows an assessment of extreme regional climate changes. Meteorological and hydrological warm period droughts were analyzed in this study. Meteorological droughts were identified using the standardized precipitation index, and hydrological droughts using the streamflow drought index. The whole river basin was analyzed over the period from 1961 to 2010. Precipitation data from Vilnius meteorological station (from 1887) and discharge data from Smalininkai (Neman) hydrological station (from 1811) were used for an evaluation of meteorological and hydrological drought recurrence over a long-term period. It was found that the total area dryness has decreased over the last 50 years. A statistically significant increase in standardized precipitation index values was observed in some river sub-basins. An analysis of drought recurrence dynamics showed that there was no indication that the number of dangerous drought was increased. It was determined that the standardized precipitation index cannot successfully identify the hydrological summer droughts in an area where the spring snowmelt forms a large part of the annual flow. In particular, the weak relationship between the indices was recorded in the first half of the summer, when a large part of the river runoff depends on accumulated water during the spring thaw. (letter)

STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS

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Jorge Machado Damázio

2015-08-01

Full Text Available DOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.

Natural gas price uncertainty and the cost-effectiveness of hedging against low hydropower revenues caused by drought

Science.gov (United States)

Kern, Jordan D.; Characklis, Gregory W.; Foster, Benjamin T.

2015-04-01

Prolonged periods of low reservoir inflows (droughts) significantly reduce a hydropower producer's ability to generate both electricity and revenues. Given the capital intensive nature of the electric power industry, this can impact hydropower producers' ability to pay down outstanding debt, leading to credit rating downgrades, higher interests rates on new debt, and ultimately, greater infrastructure costs. One potential tool for reducing the financial exposure of hydropower producers to drought is hydrologic index insurance, in particular, contracts structured to payout when streamflows drop below a specified level. An ongoing challenge in developing this type of insurance, however, is minimizing contracts' "basis risk," that is, the degree to which contract payouts deviate in timing and/or amount from actual damages experienced by policyholders. In this paper, we show that consideration of year-to-year changes in the value of hydropower (i.e., the cost of replacing it with an alternative energy source during droughts) is critical to reducing contract basis risk. In particular, we find that volatility in the price of natural gas, a key driver of peak electricity prices, can significantly degrade the performance of index insurance unless contracts are designed to explicitly consider natural gas prices when determining payouts. Results show that a combined index whose value is derived from both seasonal streamflows and the spot price of natural gas yields contracts that exhibit both lower basis risk and greater effectiveness in terms of reducing financial exposure.

Drought propagation and its relation with catchment biophysical characteristics

Science.gov (United States)

Alvarez-Garreton, C. D.; Lara, A.; Garreaud, R. D.

2016-12-01

Droughts propagate in the hydrological cycle from meteorological to soil moisture to hydrological droughts. To understand the drivers of this process is of paramount importance since the economic and societal impacts in water resources are directly related with hydrological droughts (and not with meteorological droughts, which have been most studied). This research analyses drought characteristics over a large region and identify its main exogenous (climate forcing) and endogenous (biophysical characteristics such as land cover type and topography) explanatory factors. The study region is Chile, which covers seven major climatic subtypes according to Köppen system, it has unique geographic characteristics, very sharp topography and a wide range of landscapes and vegetation conditions. Meteorological and hydrological droughts (deficit in precipitation and streamflow, respectively) are characterized by their durations and standardized deficit volumes using a variable threshold method, over 300 representative catchments (located between 27°S and 50°S). To quantify the propagation from meteorological to hydrological drought, we propose a novel drought attenuation index (DAI), calculated as the ratio between the meteorological drought severity slope and the hydrological drought severity slope. DAI varies from zero (catchment that attenuates completely a meteorological drought) to one (the meteorological drought is fully propagated through the hydrological cycle). This novel index provides key (and comparable) information about drought propagation over a wide range of different catchments, which has been highlighted as a major research gap. Similar drought indicators across the wide range of catchments are then linked with catchment biophysical characteristics. A thorough compilation of land cover information (including the percentage of native forests, grass land, urban and industrial areas, glaciers, water bodies and no vegetated areas), catchment physical

The Global Streamflow Indices and Metadata Archive (GSIM – Part 1: The production of a daily streamflow archive and metadata

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H. X. Do

2018-04-01

Full Text Available This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM, a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections. It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477: (1 a GSIM catalogue collating basic metadata associated with each time series, (2 catchment boundaries for the contributing area of each gauge, and (3 catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

Science.gov (United States)

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.

2009-01-01

In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.

The Global Streamflow Indices and Metadata Archive (GSIM) - Part 1: The production of a daily streamflow archive and metadata

Science.gov (United States)

Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth

2018-04-01

This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

High-resolution near real-time drought monitoring in South Asia

OpenAIRE

Aadhar, Saran; Mishra, Vimal

2017-01-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to m...

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

Science.gov (United States)

Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.

2011-01-01

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational

Development and application of a short- /long-term composited drought index in the upper Huaihe River basin, China

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M. Yu

2015-06-01

Full Text Available Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a short-term/long-term composited drought index (CDI which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The short-term CDI was developed by the Principle Component Analysis of the self-calibrating Palmer Drought Severity Index (sc-PDSI, the 1- and 3-month Standardized Precipitation Evapotranspiration Index (SPEI, Z Index (ZIND, the Soil Moisture Index (SMI with the long-term CDI being formulated by use of the self-calibrating Palmer Hydrology Drought Index (sc-PHDI, the 6-, 12-, 18- and 24-month SPEI, the Standardized Streamflow Index (SSI, the SMI. The sc-PDSI, the PHDI, the ZIND, the SPEI on a monthly time scale were calculated based on the monthly air temperature and precipitation, and the monthly SMI and SSI were computed based on the simulated soil moisture and runoff by the distributed Xinanjiang model. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDIs was investigated against the scPDSI, the SPEI and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition while the latter better at judging the changing trend of drought over a long time period.

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin.

Science.gov (United States)

Li, Ping; Omani, Nina; Chaubey, Indrajeet; Wei, Xiaomei

2017-05-08

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index ( SPI ), standardized soil water content index ( SSWI ), and standardized streamflow index ( SSI ). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI 12 than SPI 12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to

Spatiotemporal patterns of drought at various time scales in Shandong Province of Eastern China

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Zuo, Depeng; Cai, Siyang; Xu, Zongxue; Li, Fulin; Sun, Wenchao; Yang, Xiaojing; Kan, Guangyuan; Liu, Pin

2018-01-01

The temporal variations and spatial patterns of drought in Shandong Province of Eastern China were investigated by calculating the standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, 6-, 12-, and 24-month time scales. Monthly precipitation and air temperature time series during the period 1960-2012 were collected at 23 meteorological stations uniformly distributed over the region. The non-parametric Mann-Kendall test was used to explore the temporal trends of precipitation, air temperature, and the SPEI drought index. S-mode principal component analysis (PCA) was applied to identify the spatial patterns of drought. The results showed that an insignificant decreasing trend in annual total precipitation was detected at most stations, a significant increase of annual average air temperature occurred at all the 23 stations, and a significant decreasing trend in the SPEI was mainly detected at the coastal stations for all the time scales. The frequency of occurrence of extreme and severe drought at different time scales generally increased with decades; higher frequency and larger affected area of extreme and severe droughts occurred as the time scale increased, especially for the northwest of Shandong Province and Jiaodong peninsular. The spatial pattern of drought for SPEI-1 contains three regions: eastern Jiaodong Peninsular and northwestern and southern Shandong. As the time scale increased to 3, 6, and 12 months, the order of the three regions was transformed into another as northwestern Shandong, eastern Jiaodong Peninsular, and southern Shandong. For SPEI-24, the location identified by REOF1 was slightly shifted from northwestern Shandong to western Shandong, and REOF2 and REOF3 identified another two weak patterns in the south edge and north edge of Jiaodong Peninsular, respectively. The potential causes of drought and the impact of drought on agriculture in the study area have also been discussed. The temporal variations and spatial patterns

Spatial Correlation Of Streamflows: An Analytical Approach

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Betterle, A.; Schirmer, M.; Botter, G.

2016-12-01

The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the

Drought Forecasting Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS, Drought Time Series and Climate Indices For Next Coming Year, (Case Study: Zahedan

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Hossein Hosseinpour Niknam

2012-07-01

Full Text Available In this research in order to forecast drought for the next coming year in Zahedan, using previous Standardized Precipitation Index (SPI data and 19 other climate indices were used.  For this purpose Adaptive Neuro-Fuzzy Inference System (ANFIS was applied to build the predicting model and SPI drought index for drought quantity.  At first calculating correlation approach for analysis between droughts and climate indices was used and the most suitable indices were selected. In the next stage drought prediction for period of 12 months was done. Different combinations among input variables in ANFIS models were entered. SPI drought index was the output of the model.  The results showed that just using time series like the previous year drought SPI index in forecasting the 12 month drought was effective. However among all climate indices that were used, Nino4 showed the most suitable results.

Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows

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Srivastav, R. K.; Srinivasan, K.; Sudheer, K.

2009-05-01

Synthetic streamflow data generation involves the synthesis of likely streamflow patterns that are statistically indistinguishable from the observed streamflow data. The various kinds of stochastic models adopted for multi-season streamflow generation in hydrology are: i) parametric models which hypothesize the form of the periodic dependence structure and the distributional form a priori (examples are PAR, PARMA); disaggregation models that aim to preserve the correlation structure at the periodic level and the aggregated annual level; ii) Nonparametric models (examples are bootstrap/kernel based methods), which characterize the laws of chance, describing the stream flow process, without recourse to prior assumptions as to the form or structure of these laws; (k-nearest neighbor (k-NN), matched block bootstrap (MABB)); non-parametric disaggregation model. iii) Hybrid models which blend both parametric and non-parametric models advantageously to model the streamflows effectively. Despite many of these developments that have taken place in the field of stochastic modeling of streamflows over the last four decades, accurate prediction of the storage and the critical drought characteristics has been posing a persistent challenge to the stochastic modeler. This is partly because, usually, the stochastic streamflow model parameters are estimated by minimizing a statistically based objective function (such as maximum likelihood (MLE) or least squares (LS) estimation) and subsequently the efficacy of the models is being validated based on the accuracy of prediction of the estimates of the water-use characteristics, which requires large number of trial simulations and inspection of many plots and tables. Still accurate prediction of the storage and the critical drought characteristics may not be ensured. In this study a multi-objective optimization framework is proposed to find the optimal hybrid model (blend of a simple parametric model, PAR(1) model and matched block

Streamflow alteration at selected sites in Kansas

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Juracek, Kyle E.; Eng, Ken

2017-06-26

An understanding of streamflow alteration in response to various disturbances is necessary for the effective management of stream habitat for a variety of species in Kansas. Streamflow alteration can have negative ecological effects. Using a modeling approach, streamflow alteration was assessed for 129 selected U.S. Geological Survey streamgages in the State for which requisite streamflow and basin-characteristic information was available. The assessment involved a comparison of the observed condition from 1980 to 2015 with the predicted expected (least-disturbed) condition for 29 streamflow metrics. The metrics represent various characteristics of streamflow including average flow (annual, monthly) and low and high flow (frequency, duration, magnitude).Streamflow alteration in Kansas was indicated locally, regionally, and statewide. Given the absence of a pronounced trend in annual precipitation in Kansas, a precipitation-related explanation for streamflow alteration was not supported. Thus, the likely explanation for streamflow alteration was human activity. Locally, a flashier flow regime (typified by shorter lag times and more frequent and higher peak discharges) was indicated for three streamgages with urbanized basins that had higher percentages of impervious surfaces than other basins in the State. The combination of localized reservoir effects and regional groundwater pumping from the High Plains aquifer likely was responsible, in part, for diminished conditions indicated for multiple streamflow metrics in western and central Kansas. Statewide, the implementation of agricultural land-management practices to reduce runoff may have been responsible, in part, for a diminished duration and magnitude of high flows. In central and eastern Kansas, implemented agricultural land-management practices may have been partly responsible for an inflated magnitude of low flows at several sites.

SDI and Markov Chains for Regional Drought Characteristics

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Chen-Feng Yeh

2015-08-01

Full Text Available In recent years, global climate change has altered precipitation patterns, causing uneven spatial and temporal distribution of precipitation that gradually induces precipitation polarization phenomena. Taiwan is located in the subtropical climate zone, with distinct wet and dry seasons, which makes the polarization phenomenon more obvious; this has also led to a large difference between river flows during the wet and dry seasons, which is significantly influenced by precipitation, resulting in hydrological drought. Therefore, to effectively address the growing issue of water shortages, it is necessary to explore and assess the drought characteristics of river systems. In this study, the drought characteristics of northern Taiwan were studied using the streamflow drought index (SDI and Markov chains. Analysis results showed that the year 2002 was a turning point for drought severity in both the Lanyang River and Yilan River basins; the severity of rain events in the Lanyang River basin increased after 2002, and the severity of drought events in the Yilan River basin exhibited a gradual upward trend. In the study of drought severity, analysis results from periods of three months (November to January and six months (November to April have shown significant drought characteristics. In addition, analysis of drought occurrence probabilities using the method of Markov chains has shown that the occurrence probabilities of drought events are higher in the Lanyang River basin than in the Yilan River basin; particularly for extreme events, the occurrence probability of an extreme drought event is 20.6% during the dry season (November to April in the Lanyang River basin, and 3.4% in the Yilan River basin. This study shows that for analysis of drought/wet occurrence probabilities, the results obtained for the drought frequency and occurrence probability using short-term data with the method of Markov chains can be used to predict the long-term occurrence

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

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J. C. Ochoa-Rivera

2002-01-01

Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..

Investigation of the complexity of streamflow fluctuations in a large heterogeneous lake catchment in China

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Ye, Xuchun; Xu, Chong-Yu; Li, Xianghu; Zhang, Qi

2018-05-01

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h( q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h( q). However, the relationship between the width of the singularity spectrum (Δ α) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.

Extreme Drought-induced Trend Changes in MODIS EVI Time Series in Yunnan, China

International Nuclear Information System (INIS)

Huang, Kaicheng; Zhou, Tao; Zhao, Xiang

2014-01-01

Extreme climatic events triggered by global climate change are expected to increase significantly hence research into vegetation response is crucial to evaluate environmental risk. Yunnan province, locating in southwest China, experienced an extreme drought event (from autumn of 2009 to spring of 2010), with the lowest percentage rainfall anomaly and the longest non-rain days in the past 50 years. This study aimed to explore the characteristics and differences in the response to drought of four land cover types in Yunnan province, including forest, grassland, shrub, and cropland during the period 2001-2011. We used remote sensing data, MODIS-derived EVI (Enhanced Vegetation Index) to study the vegetation responses to this extreme drought event. The EVI time series were decomposed into trend, seasonal and remainder components using BFAST (Breaks For Additive Seasonal and Trend) which accounts for seasonality and enables the detection of trend changes within the time series. The preliminary results showed that: (1) BFAST proved to be capable of detecting drought-induced trend changes in EVI time series. (2) Changes in the trend component over time consisted of both gradual and abrupt changes. (3) Different spatial patterns were found for abrupt and gradual changes. (4) Cropland exhibited an abrupt change, due to its sensitivity to severe drought, while the forest seemed least affected by the extreme drought

Streamflow characteristics at hydrologic bench-mark stations

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Lawrence, C.L.

1987-01-01

The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.

Effect of monthly areal rainfall uncertainty on streamflow simulation

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Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

Climate Projections and Drought: Verification for the Colorado River Basin

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Santos, N. I.; Piechota, T. C.; Miller, W. P.; Ahmad, S.

2017-12-01

The Colorado River Basin has experienced the driest 17 year period (2000-2016) in over 100 years of historical record keeping. While the Colorado River reservoir system began the current drought at near 100% capacity, reservoir storage has fallen to just above 50% during the drought. Even though federal and state water agencies have worked together to mitigate the impact of the drought and have collaboratively sponsored conservation programs and drought contingency plans, the 17-years of observed data beg the question as to whether the most recent climate projections would have been able to project the current drought's severity. The objective of this study is to analyze observations and ensemble projections (e.g. temperature, precipitation, streamflow) from the CMIP3 and CMIP5 archive in the Colorado River Basin and compare metrics related to skill scores, the Palmer Drought Severity Index, and water supply sustainability index. Furthermore, a sub-ensemble of CMIP3/CMIP5 projections, developed using a teleconnection replication verification technique developed by the author, will also be compared to the observed record to assist in further validating the technique as a usable process to increase skill in climatological projections. In the end, this study will assist to better inform water resource managers about the ability of climate ensembles to project hydroclimatic variability and the appearance of decadal drought periods.

Detection and attribution of streamflow timing changes to climate change in the Western United States

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Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.

2009-01-01

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

Space-time trends in U.S. meteorological droughts

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Poulomi Ganguli

2016-12-01

New hydrological insights for the region: The paper finds spatial coverage of extreme meteorological drought in the recent years (post-2010 exceeds that of the iconic droughts of the 1930s (the Dust Bowl era, and the 1950s. These results are in contrast with trends in spatial variance that does not exhibit any statistically significant trend. In addition, we find drought persistence remains relatively stationary over the last half century. The findings can inform drought monitoring and planning, and improve future drought resilience.

Satellite-based Drought Reporting on the Navajo Nation

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McCullum, A. J. K.; Schmidt, C.; Ly, V.; Green, R.; McClellan, C.

2017-12-01

The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

Spatiotemporal Drought Analysis and Drought Indices Comparison in India

Science.gov (United States)

Janardhanan, A.

2017-12-01

Droughts and floods are an ever-occurring phenomenon that has been wreaking havoc on humans since the start of time. As droughts are on a very large scale, studying them within a regional context can minimize confounding factors such as climate change. Droughts and floods are extremely erratic and very difficult to predict and therefore necessitate modeling through advanced statistics. The SPI (Standard Precipitation Index) and the SPEI (Standard Precipitation Evapotranspiration Index) are two ways to temporally model drought and flood patterns across each metrological sub basin in India over a variety of different time scales. SPI only accounts for precipitation values, while the SPEI accounts for both precipitation and temperature and is commonly regarded as a more reliable drought index. Using monthly rainfall and temperature data from 1871-2016, these two indices were calculated. The results depict the drought and flood severity index, length of drought, and average SPI or SPEI value for each meteorological sub region in India. A Wilcox Ranksum test was then conducted to determine whether these two indices differed over the long term for drought analysis. The drought return periods were analyzed to determine if the population mean differed between the SPI and SPEI values. Our analysis found no statistical difference between SPI and SPEI with regards to long-term drought analysis. This indicates that temperature is not needed when modeling drought on a long-term time scale and that SPI is just as effective as SPEI, which has the potential to save a lot of time and resources on calculating drought indices.

Analysis of potential errors in real-time streamflow data and methods of data verification by digital computer

Science.gov (United States)

Lystrom, David J.

1972-01-01

The magnitude, frequency, and types of errors inherent in real-time streamflow data are presented in part I. It was found that real-time data are generally less accurate than are historical data, primarily because real-time data are often used before errors can be detected and corrections applied.

Individual traits as determinants of time to death under extreme drought in Pinus sylvestris L.

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Garcia-Forner, Núria; Sala, Anna; Biel, Carme; Savé, Robert; Martínez-Vilalta, Jordi

2016-10-01

Plants exhibit a variety of drought responses involving multiple interacting traits and processes, which makes predictions of drought survival challenging. Careful evaluation of responses within species, where individuals share broadly similar drought resistance strategies, can provide insight into the relative importance of different traits and processes. We subjected Pinus sylvestris L. saplings to extreme drought (no watering) leading to death in a greenhouse to (i) determine the relative effect of predisposing factors and responses to drought on survival time, (ii) identify and rank the importance of key predictors of time to death and (iii) compare individual characteristics of dead and surviving trees sampled concurrently. Time until death varied over 3 months among individual trees (from 29 to 147 days). Survival time was best predicted (higher explained variance and impact on the median survival time) by variables related to carbon uptake and carbon/water economy before and during drought. Trees with higher concentrations of monosaccharides before the beginning of the drought treatment and with higher assimilation rates prior to and during the treatment survived longer (median survival time increased 25-70 days), even at the expense of higher water loss. Dead trees exhibited less than half the amount of nonstructural carbohydrates (NSCs) in branches, stem and relative to surviving trees sampled concurrently. Overall, our results indicate that the maintenance of carbon assimilation to prevent acute depletion of NSC content above some critical level appears to be the main factor explaining survival time of P. sylvestris trees under extreme drought. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development of streamflow projections under changing climate conditions over Colorado River basin headwaters

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W. P. Miller

2011-07-01

Full Text Available The current drought over the Colorado River Basin has raised concerns that the US Department of the Interior, Bureau of Reclamation (Reclamation may impose water shortages over the lower portion of the basin for the first time in history. The guidelines that determine levels of shortage are affected by relatively short-term (3 to 7 month forecasts determined by the Colorado Basin River Forecast Center (CBRFC using the National Weather Service (NWS River Forecasting System (RFS hydrologic model. While these forecasts by the CBRFC are useful, water managers within the basin are interested in long-term projections of streamflow, particularly under changing climate conditions. In this study, a bias-corrected, statistically downscaled dataset of projected climate is used to force the NWS RFS utilized by the CBRFC to derive projections of streamflow over the Green, Gunnison, and San Juan River headwater basins located within the Colorado River Basin. This study evaluates the impact of changing climate to evapotranspiration rates and contributes to a better understanding of how hydrologic processes change under varying climate conditions. The impact to evapotranspiration rates is taken into consideration and incorporated into the development of streamflow projections over Colorado River headwater basins in this study. Additionally, the NWS RFS is modified to account for impacts to evapotranspiration due to changing temperature over the basin. Adjusting evapotranspiration demands resulted in a 6 % to 13 % average decrease in runoff over the Gunnison River Basin when compared to static evapotranspiration rates. Streamflow projections derived using projections of future climate and the NWS RFS provided by the CBRFC resulted in decreased runoff in 2 of the 3 basins considered. Over the Gunnison and San Juan River basins, a 10 % to 15 % average decrease in basin runoff is projected through the year 2099. However, over the Green River basin, a 5 % to 8

Effect of Modulation of ENSO by Decadal and Multidecadal Ocean-Atmospheric Oscillations on Continental US Streamflows

Science.gov (United States)

Singh, S.; Abebe, A.; Srivastava, P.; Chaubey, I.

2017-12-01

Evaluation of the influences of individual and coupled oceanic-atmospheric oscillations on streamflow at a regional scale in the United States is the focus of this study. The main climatic oscillations considered in this study are: El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). Unimpacted or minimally impacted by water management streamflow data from the Model Parameter Estimation Experiment (MOPEX) were used in this study. Two robust and novel non-parametric tests, namely, the rank based partial least square (PLS) and the Joint Rank Fit (JRFit) procedures were used to identify the individual and coupled effect of oscillations on streamflow across continental U.S. (CONUS), respectively. Moreover, the interactive effects of ENSO with decadal and multidecadal cycles were tested and quantified using the JRFit interaction test. The analysis of ENSO indicated higher streamflows during La Niña phase compared to the El Niño phase in Northwest, Northeast and the lower part of Ohio Valley while the opposite occurs for rest of the climatic regions in US. Two distinct climate regions (Northwest and Southeast) were identified from the PDO analysis where PDO negative phase results in increased streamflow than PDO positive phase. Consistent negative and positive correlated regions around the CONUS were identified for AMO and NAO, respectively. The interaction test of ENSO with decadal and multidecadal oscillations showed that El Niño is modulated by the negative phase of PDO and NAO, and the positive phase of AMO, respectively, in the Upper Midwest. However, La Niña is modulated by the positive phase of AMO and PDO in Ohio Valley and Northeast while in Southeast and the South it is modulated by AMO negative phase. Results of this study will assist water managers to understand the streamflow change patterns across the CONUS at decadal and multi-decadal time scales. The

Understanding and seasonal forecasting of hydrological drought in the Anthropocene

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X. Yuan

2017-11-01

Full Text Available Hydrological drought is not only caused by natural hydroclimate variability but can also be directly altered by human interventions including reservoir operation, irrigation, groundwater exploitation, etc. Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges due to complicated interactions among climate, hydrology and humans. In this paper, five decades (1961–2010 of naturalized and observed streamflow datasets are used to investigate hydrological drought characteristics in a heavily managed river basin, the Yellow River basin in north China. Human interventions decrease the correlation between hydrological and meteorological droughts, and make the hydrological drought respond to longer timescales of meteorological drought. Due to large water consumptions in the middle and lower reaches, there are 118–262 % increases in the hydrological drought frequency, up to 8-fold increases in the drought severity, 21–99 % increases in the drought duration and the drought onset is earlier. The non-stationarity due to anthropogenic climate change and human water use basically decreases the correlation between meteorological and hydrological droughts and reduces the effect of human interventions on hydrological drought frequency while increasing the effect on drought duration and severity. A set of 29-year (1982–2010 hindcasts from an established seasonal hydrological forecasting system are used to assess the forecast skill of hydrological drought. In the naturalized condition, the climate-model-based approach outperforms the climatology method in predicting the 2001 severe hydrological drought event. Based on the 29-year hindcasts, the former method has a Brier skill score of 11–26 % against the latter for the probabilistic hydrological drought forecasting. In the Anthropocene, the skill for both approaches increases due to the dominant influence of human interventions that have been implicitly

Possible Future Climate Change Impacts on the Hydrological Drought Events in the Weihe River Basin, China

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Fei Yuan

2016-01-01

Full Text Available Quantitative evaluation of future climate change impacts on hydrological drought characteristics is one of important measures for implementing sustainable water resources management and effective disaster mitigation in drought-prone regions under the changing environment. In this study, a modeling system for projecting the potential future climate change impacts on hydrological droughts in the Weihe River basin (WRB in North China is presented. This system consists of a large-scale hydrological model driven by climate outputs from three climate models (CMs for future streamflow projections, a probabilistic model for univariate drought assessment, and a copula-based bivariate model for joint drought frequency analysis under historical and future climates. With the observed historical climate data as the inputs, the Variable Infiltration Capacity hydrological model projects an overall runoff reduction in the WRB under the Intergovernmental Panel on Climate Change A1B scenario. The univariate drought assessment found that although fewer hydrological drought events would occur under A1B scenario, drought duration and severity tend to increase remarkably. Moreover, the bivariate drought assessment reveals that future droughts in the same return period as the baseline droughts would become more serious. With these trends in the future, the hydrological drought situation in the WRB would be further deteriorated.

Impacts of climate change on vegetation, hydrological and socio-economic droughts in a transitional wet-to-dry Mediterranean region

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Nunes, João Pedro; Pulquério, Mário; Grosso, Nuno; Duarte Santos, Filipe; João Cruz, Maria

2015-04-01

The Tagus river basin is located in a transitional region between humid and semi-arid climate. The lower part of the basin is a strategic source of water for Portugal, providing water for agricultural irrigation, hydropower generation, and domestic water supplies for over 4 million people. Climate change in this region is expected to lead to higher temperatures and lower rainfall, therefore increasing climatic aridity. In this transitional region, this could lead to an increased frequency of severe droughts, threatening climatic support for current agricultural and forestry practices, as well as the sustainability of domestic water supplies. This work evaluated the impacts of climate change on drought frequency and severity for the Portuguese part of the Tagus river basin. Climate change scenarios for 2010-2100 (A2 greenhouse emission scenarios) were statistically downscaled for the study area. They were evaluated with the Soil and Water Assessment Tool (SWAT) eco-hydrological model, which simulated vegetation water demand and drought stress, soil water availability, irrigation abstraction, streamflow, reservoir storage and groundwater recharge. Water inflows from Spain were estimated using an empirical climate-based model. Drought occurrence and severity was analyzed in terms of: * meteorological drought, based on (i) the Standardized Precipitation Index and (ii) the Aridity Index; * vegetation/agricultural drought, based on plant water stress; * hydrological drought, based on (i) streamflow rates and (ii) reservoir storage; * socio-economic drought, based on (i) the capacity of the main reservoir in the system (Castelo de Bode) to sustain hydropower and domestic supplies, and (ii) the rate of groundwater extraction vs. irrigation demands for the cultures located in the intensive cultivation regions of the Lezírias near the Tagus estuary. The results indicate a trend of increasing frequency and severity of most drought types during the XXIst century, with a

Mississippi River streamflow measurement techniques at St. Louis, Missouri

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Wastson, Chester C.; Holmes, Robert R.; Biedenham, David S.

2013-01-01

Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.

Water Storage, Mixing and Transit Times During a Multiyear Drought.

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Van der Velde, Y.; Visser, A.; Thaw, M.; Safeeq, M.

2017-12-01

From 2012 to 2016, a five year intensive drought occurred in the Californian Sierra Nevada. We use this drought period as an opportunity to investigate how catchment water storage, mixing and transit times changes from wet to dry conditions using long term datasets of river discharge, evapotranspiration, water quality, and multiple cosmogenic radioactive isotopes. Characteristic features of the test catchment (4.6 km2 , altitude 1660-2117 m) include a thick (>5m) unsaturated zone in deeply weathered granite mountain soils, snow melt and events of high intensity rainfall, dry summers and numerous wetland meadows along the stream. Our data and model analysis suggest that under drought conditions, river flow predominantly consist of deep groundwater tapped by deeply incised sections of the stream, while the wetlands hold on to their water just below the root system of its shallow rooting vegetation. In contrast, during wet periods, most runoff is generated on the flat riparian wetland meadows, while the regional groundwater system slowly refills itself as water makes its way through the thick unsaturated zones. Antecedent wet or dry years play an crucial role as antecedent wet years cause a substantial regional groundwater flow towards the riparian wetlands, filling up the riparian wetlands and yielding a much stronger discharge response of the wetlands to rainfall events than under antecedent dry years This interaction between the regional groundwater system and the local wetland systems weakens as the drought progresses and regional groundwater flow to the wetlands lessens. Although, due to the wet events in 2016-2017, the catchment fills up rapidly to pre-drought conditions, we show that water transit times and therefore likely the water quality will contain drought signs for several years to come. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS- XXXXXX

Long-range forecasting of intermittent streamflow

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van Ogtrop, F. F.; Vervoort, R. W.; Heller, G. Z.; Stasinopoulos, D. M.; Rigby, R. A.

2011-11-01

Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

Long-range forecasting of intermittent streamflow

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F. F. van Ogtrop

2011-11-01

Full Text Available Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

Hydrological change: Towards a consistent approach to assess changes on both floods and droughts

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Quesada-Montano, Beatriz; Di Baldassarre, Giuliano; Rangecroft, Sally; Van Loon, Anne F.

2018-01-01

Several studies have found that the frequency, magnitude and spatio-temporal distribution of droughts and floods have significantly increased in many regions of the world. Yet, most of the methods used in detecting trends in hydrological extremes 1) focus on either floods or droughts, and/or 2) base their assessment on characteristics that, even though useful for trend identification, cannot be directly used in decision making, e.g. integrated water resources management and disaster risk reduction. In this paper, we first discuss the need for a consistent approach to assess changes on both floods and droughts, and then propose a method based on the theory of runs and threshold levels. Flood and drought changes were assessed in terms of frequency, length and surplus/deficit volumes. This paper also presents an example application using streamflow data from two hydrometric stations along the Po River basin (Italy), Piacenza and Pontelagoscuro, and then discuss opportunities and challenges of the proposed method.

Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

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Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

2015-05-01

Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Identifying needs for streamflow forecasting in the Incomati basin, Southern Africa

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Sunday, Robert; Werner, Micha; Masih, Ilyas; van der Zaag, Pieter

2013-04-01

Despite being widely recognised as an efficient tool in the operational management of water resources, rainfall and streamflow forecasts are currently not utilised in water management practice in the Incomati Basin in Southern Africa. Although, there have been initiatives for forecasting streamflow in the Sabie and Crocodile sub-basins, the outputs of these have found little use because of scepticism on the accuracy and reliability of the information, or the relevance of the information provided to the needs of the water managers. The process of improving these forecasts is underway, but as yet the actual needs of the forecasts are unclear and scope of the ongoing initiatives remains very limited. In this study questionnaires and focused group interviews were used to establish the need, potential use, benefit and required accuracy of rainfall and streamflow forecasts in the Incomati Basin. Thirty five interviews were conducted with professionals engaged in water sector and detailed discussions were held with water institutions, including the Inkomati Catchment Management Agency (ICMA), Komati Basin Water Authority (KOBWA), South African Weather Service (SAWS), water managers, dam operators, water experts, farmers and other water users in the Basin. Survey results show that about 97% of the respondents receive weather forecasts. In contrast to expectations, only 5% have access to the streamflow forecast. In the weather forecast, the most important variables were considered to be rainfall and temperature at daily and weekly time scales. Moreover, forecasts of global climatic indices such as El Niño or La Niña were neither received nor demanded. There was limited demand and/or awareness of flood and drought forecasts including the information on their linkages with global climatic indices. While the majority of respondents indicate the need and indeed use the weather forecast, the provision, communication and interpretation were in general found to be with too

Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

Science.gov (United States)

Jaeger, K. L.

2017-12-01

The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the

Potential impact of climate change to the future streamflow of Yellow River Basin based on CMIP5 data

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Yang, Xiaoli; Zheng, Weifei; Ren, Liliang; Zhang, Mengru; Wang, Yuqian; Liu, Yi; Yuan, Fei; Jiang, Shanhu

2018-02-01

The Yellow River Basin (YRB) is the largest river basin in northern China, which has suffering water scarcity and drought hazard for many years. Therefore, assessments the potential impacts of climate change on the future streamflow in this basin is very important for local policy and planning on food security. In this study, based on the observations of 101 meteorological stations in YRB, equidistant CDF matching (EDCDFm) statistical downscaling approach was applied to eight climate models under two emissions scenarios (RCP4.5 and RCP8.5) from phase five of the Coupled Model Intercomparison Project (CMIP5). Variable infiltration capacity (VIC) model with 0.25° × 0.25° spatial resolution was developed based on downscaled fields for simulating streamflow in the future period over YRB. The results show that with the global warming trend, the annual streamflow will reduced about 10 % during the period of 2021-2050, compared to the base period of 1961-1990 in YRB. There should be suitable water resources planning to meet the demands of growing populations and future climate changing in this region.

More than just consumers: Integrating local observations into drought monitoring to better support decision making

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Ferguson, D. B.; Masayesva, A.; Meadow, A. M.; Crimmins, M.

2016-12-01

Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. In arid and semi-arid regions of the world, this challenge is particularly acute since social-ecological systems are already well-adapted to dry conditions. Understanding what drought means in these regions is an important first step in developing a decision-relevant monitoring system. Traditional drought indices may be of some use, but local observations may ultimately be more relevant for informing difficult decisions in response to unusually dry conditions. This presentation will focus on insights gained from a collaborative project between the University of Arizona and the Hopi Tribe-a Native American community in the U.S. Southwest-to develop a drought information system that is responsive to local needs. The primary goal of the project was to develop a system that: is based on how drought is experienced by Hopi citizens and resource managers, can incorporate local observations of drought impacts as well as conventional indicators, and brings together local expertise with conventional science-based observations. This kind of drought monitoring system can harnesses as much available information as possible to inform resource managers, political leaders, and citizens about drought conditions, but such a system can also engage these local drought stakeholders in observing, thinking about, and helping guide planning for drought.

Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

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Orth, R.; Seneviratne, S. I.

2013-10-01

As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

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R. Orth

2013-10-01

Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

Multi-site Stochastic Simulation of Daily Streamflow with Markov Chain and KNN Algorithm

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Mathai, J.; Mujumdar, P.

2017-12-01

A key focus of this study is to develop a method which is physically consistent with the hydrologic processes that can capture short-term characteristics of daily hydrograph as well as the correlation of streamflow in temporal and spatial domains. In complex water resource systems, flow fluctuations at small time intervals require that discretisation be done at small time scales such as daily scales. Also, simultaneous generation of synthetic flows at different sites in the same basin are required. We propose a method to equip water managers with a streamflow generator within a stochastic streamflow simulation framework. The motivation for the proposed method is to generate sequences that extend beyond the variability represented in the historical record of streamflow time series. The method has two steps: In step 1, daily flow is generated independently at each station by a two-state Markov chain, with rising limb increments randomly sampled from a Gamma distribution and the falling limb modelled as exponential recession and in step 2, the streamflow generated in step 1 is input to a nonparametric K-nearest neighbor (KNN) time series bootstrap resampler. The KNN model, being data driven, does not require assumptions on the dependence structure of the time series. A major limitation of KNN based streamflow generators is that they do not produce new values, but merely reshuffle the historical data to generate realistic streamflow sequences. However, daily flow generated using the Markov chain approach is capable of generating a rich variety of streamflow sequences. Furthermore, the rising and falling limbs of daily hydrograph represent different physical processes, and hence they need to be modelled individually. Thus, our method combines the strengths of the two approaches. We show the utility of the method and improvement over the traditional KNN by simulating daily streamflow sequences at 7 locations in the Godavari River basin in India.

Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings

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Ravindranath, A.; Devineni, N.

2016-12-01

Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.

Global patterns of drought recovery

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Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-09

Drought is a recurring multi-factor phenomenon with major impacts on natural and human systems1-3. Drought is especially important for land carbon sink variability, influencing climate regulation of the terrestrial biosphere4. While 20th Century trends in drought regime are ambiguous, “more extreme extremes” as well as more frequent and severe droughts3,7 are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the spatiotemporal patterning and controls of drought recovery are largely unknown. Here we use three distinct global datasets of gross primary productivity to show that across diverse terrestrial ecosystems drought recovery times are driven by biological productivity and biodiversity, with drought length and severity of secondary importance. Recovery time, especially for extreme droughts, and the areal extent of ecosystems in recovery from drought generally increase over the 20th Century, supporting an increase globally in drought impact8. Our results indicate that if future Anthropocene droughts become more widespread as expected, that droughts will become more frequent relative to recovery time. This increases the risk of entering a new regime where vegetation never recovers to its original state and widespread degradation of the land carbon sink ensues.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

Science.gov (United States)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio

Science.gov (United States)

Koltun, G.F.

2015-01-01

Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series.

New insights on historic droughts in the UK: Analysis of 200 river flow reconstructions for 1890-2015

Science.gov (United States)

Parry, Simon; Barker, Lucy; Hannaford, Jamie; Prudhomme, Christel; Smith, Katie; Svensson, Cecilia; Tanguy, Maliko

2017-04-01

oceanic index patterns as potential drivers of streamflow drought. The quantification of changes over time in both the mean and the variability of drought frequency, duration, severity and termination benefits from the temporal extent of the river flow reconstructions, assessing the temporal variability of drought over more prolonged timescales than previous drought trend studies. When considered alongside complimentary reconstructions of rainfall and groundwater levels, the characteristics of propagation from meteorological to hydrological drought are analysed to an extent not previously possible. The unprecedented spatio-temporal coverage of the river flow reconstructions has yielded important new insights on historic droughts in the UK. It is hoped that this more robust assessment of the historical variability of hydrological drought in the UK will underpin enhanced drought planning and management.

Drivers influencing streamflow changes in the Upper Turia basin, Spain.

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Salmoral, Gloria; Willaarts, Bárbara A; Troch, Peter A; Garrido, Alberto

2015-01-15

Many rivers across the world have experienced a significant streamflow reduction over the last decades. Drivers of the observed streamflow changes are multiple, including climate change (CC), land use and land cover changes (LULCC), water transfers and river impoundment. Many of these drivers inter-act simultaneously, making it difficult to discern the impact of each driver individually. In this study we isolate the effects of LULCC on the observed streamflow reduction in the Upper Turia basin (east Spain) during the period 1973-2008. Regression models of annual streamflow are fitted with climatic variables and also additional time variant drivers like LULCC. The ecohydrological model SWAT is used to study the magnitude and sign of streamflow change when LULCC occurs. Our results show that LULCC does play a significant role on the water balance, but it is not the main driver underpinning the observed reduction on Turia's streamflow. Increasing mean temperature is the main factor supporting increasing evapotranspiration and streamflow reduction. In fact, LULCC and CC have had an offsetting effect on the streamflow generation during the study period. While streamflow has been negatively affected by increasing temperature, ongoing LULCC have positively compensated with reduced evapotranspiration rates, thanks to mainly shrubland clearing and forest degradation processes. These findings are valuable for the management of the Turia river basin, as well as a useful approach for the determination of the weight of LULCC on the hydrological response in other regions. Copyright © 2014 Elsevier B.V. All rights reserved.

The evolution of the monthly hydrograph under hot drought conditions in the Southwest US

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Solander, K.; Bennett, K. E.; Middleton, R. S.

2017-12-01

Hydrology will undergo unprecedented changes in the 21st century. In particular, the emergence of the hot drought—an extraordinary combination of recurring droughts coupled with warmer temperatures—will lead to more frequent and widespread droughts of longer duration. This will transform the natural and engineered landscape, with millions of dollars in critical infrastructure and investments in agriculture, municipalities, and energy-water supplies at stake. Here, we investigate how the monthly hydrograph will evolve under hot drought conditions by examining the response of streamflow under historic droughts overlaid with expected temperature increases in the coming decades. We use a suite of Global Climate Models and two emission scenarios coupled to the Variable Infiltration Capacity hydrology model to evaluate these changes under different levels of warming using various sub-basins within the Colorado River Basin as a test case. Results indicate a substantial change in both magnitude (up to 40% decrease) and timing (greater than one-month earlier) in peak flows with spatial differences strongly influenced by elevation. Findings indicate these shifts are being driven by changing snow and snowmelt patterns. Such changes are anticipated to have a substantial impact on food, energy, and water resources within the basin and are important to understand in advance given that they represent the extreme range of conditions likely to occur so we can improve the management of this resource and adapt to these changes during critical periods.

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

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Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.

2015-01-01

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

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Dudley, Robert W.

2008-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0

Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA

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Littell, Jeremy; Pederson, Gregory T.; Gray, Stephen T.; Tjoelker, Michael; Hamlet, Alan F.; Woodhouse, Connie A.

2016-01-01

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands

Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

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T. Raziei

2010-10-01

Full Text Available Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR reanalysis and the Global Precipitation Climatology Centre (GPCC dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI on 24-month time scale, while Principal Component Analysis (PCA and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings.

Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

Characterizing Drought Events from a Hydrological Model Ensemble

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Smith, Katie; Parry, Simon; Prudhomme, Christel; Hannaford, Jamie; Tanguy, Maliko; Barker, Lucy; Svensson, Cecilia

2017-04-01

Hydrological droughts are a slow onset natural hazard that can affect large areas. Within the United Kingdom there have been eight major drought events over the last 50 years, with several events acting at the continental scale, and covering the entire nation. Many of these events have lasted several years and had significant impacts on agriculture, the environment and the economy. Generally in the UK, due to a northwest-southeast gradient in rainfall and relief, as well as varying underlying geology, droughts tend to be most severe in the southeast, which can threaten water supplies to the capital in London. With the impacts of climate change likely to increase the severity and duration of drought events worldwide, it is crucial that we gain an understanding of the characteristics of some of the longer and more extreme droughts of the 19th and 20th centuries, so we may utilize this information in planning for the future. Hydrological models are essential both for reconstructing such events that predate streamflow records, and for use in drought forecasting. However, whilst the uncertainties involved in modelling hydrological extremes on the flooding end of the flow regime have been studied in depth over the past few decades, the uncertainties in simulating droughts and low flow events have not yet received such rigorous academic attention. The "Cascade of Uncertainty" approach has been applied to explore uncertainty and coherence across simulations of notable drought events from the past 50 years using the airGR family of daily lumped catchment models. Parameter uncertainty has been addressed using a Latin Hypercube sampled experiment of 500,000 parameter sets per model (GR4J, GR5J and GR6J), over more than 200 catchments across the UK. The best performing model parameterisations, determined using a multi-objective function approach, have then been taken forward for use in the assessment of the impact of model parameters and model structure on drought event

A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature

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Ahmadalipour, Ali; Moradkhani, Hamid; Demirel, Mehmet C.

2017-10-01

The changing climate and the associated future increases in temperature are expected to have impacts on drought characteristics and hydrologic cycle. This paper investigates the projected changes in spatiotemporal characteristics of droughts and their future attributes over the Willamette River Basin (WRB) in the Pacific Northwest U.S. The analysis is performed using two subsets of downscaled CMIP5 global climate models (GCMs) each consisting of 10 models from two future scenarios (RCP4.5 and RCP8.5) for 30 years of historical period (1970-1999) and 90 years of future projections (2010-2099). Hydrologic modeling is conducted using the Precipitation Runoff Modeling System (PRMS) as a robust distributed hydrologic model with lower computational cost compared to other models. Meteorological and hydrological droughts are studied using three drought indices (i.e. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Standardized Streamflow Index). Results reveal that the intensity and duration of hydrological droughts are expected to increase over the WRB, albeit the annual precipitation is expected to increase. On the other hand, the intensity of meteorological droughts do not indicate an aggravation for most cases. We explore the changes of hydrometeolorogical variables over the basin in order to understand the causes for such differences and to discover the controlling factors of drought. Furthermore, the uncertainty of projections are quantified for model, scenario, and downscaling uncertainty.

Drought propagation in the Paraná Basin, Brazil: from rainfall deficits to impacts on reservoir storage

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Melo, D. D.; Wendland, E.

2017-12-01

The sensibility and resilience of hydrologic systems to climate changes are crucial for estimating potential impacts of droughts, responsible for major economic and human losses globally. Understanding how droughts propagate is a key element to develop a predictive understanding for future management and mitigation strategies. In this context, this study investigated the drought propagation in the Paraná Basin (PB), Southeast Brazil, a major hydroelectricity producing region with 32 % (60 million people) of the country's population. Reservoir storage (RESS), river discharge (Q) and rainfall (P) data were used to assess the linkages between meteorological and hydrological droughts, characterized by the Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI), respectively. The data are from 37 sub-basins within the PB, consisting of contributing areas of 37 reservoirs (250 km3 of stored water) within the PB for the period between 1995 and 2015. The response time (RT) of the hydrologic system to droughts, given as the time lag between P, Q and RESS, was quantified using a non-parametric statistical method that combines cumulative sums and Bootstrap resampling technique. Based on our results, the RTs of the hydrologic system of the PB varies from 0 to 6 months, depending on a number of aspects: lithology, topography, dam operation, etc. Linkages between SPI and SDI indicated that the anthropogenic control (dam operation) plays an important role in buffering drought impacts to downstream sub-basins: SDI decreased from upstream to downstream despite similar SPI values over the whole area. Comparisons between sub-basins, with variable drainage sizes (5,000 - 50,000 km2), confirmed the benefice of upstream reservoirs in reducing hydrological droughts. For example, the RT for a 4,800 km2 basin was 6 months between P and Q and 9 months between Q and RESS, under anthropogenic control. Conversely, the RT to precipitation for a reservoir subjected to natural

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

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Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

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Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt

Developing drought impact functions for drought risk management

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S. Bachmair

2017-11-01

Full Text Available Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model, and an ensemble regression tree approach (random forest. The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on

A Conjunction Method of Wavelet Transform-Particle Swarm Optimization-Support Vector Machine for Streamflow Forecasting

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Fanping Zhang

2014-01-01

Full Text Available Streamflow forecasting has an important role in water resource management and reservoir operation. Support vector machine (SVM is an appropriate and suitable method for streamflow prediction due to its best versatility, robustness, and effectiveness. In this study, a wavelet transform particle swarm optimization support vector machine (WT-PSO-SVM model is proposed and applied for streamflow time series prediction. Firstly, the streamflow time series were decomposed into various details (Ds and an approximation (A3 at three resolution levels (21-22-23 using Daubechies (db3 discrete wavelet. Correlation coefficients between each D subtime series and original monthly streamflow time series are calculated. Ds components with high correlation coefficients (D3 are added to the approximation (A3 as the input values of the SVM model. Secondly, the PSO is employed to select the optimal parameters, C, ε, and σ, of the SVM model. Finally, the WT-PSO-SVM models are trained and tested by the monthly streamflow time series of Tangnaihai Station located in Yellow River upper stream from January 1956 to December 2008. The test results indicate that the WT-PSO-SVM approach provide a superior alternative to the single SVM model for forecasting monthly streamflow in situations without formulating models for internal structure of the watershed.

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

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Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2014-05-01

By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

Changing characteristics of streamflow in the Midwest and its relation to oceanic-atmospheric oscillations

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Thakur, B.; Pathak, P.; Kalra, A.; Ahmad, S.

2016-12-01

The identification of primary drivers of streamflow may prove beneficial in forecasting streamflow in the Midwestern U.S. In the past researches, streamflow in the region have been strongly correlated with El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO). The present study takes in to account the pre-defined Pacific and Atlantic Ocean regions (e.g., ENSO, PDO, AMO) along with new regions with an intent to identify new significantly correlated regions. This study assesses the interrelationship between sea surface temperatures (SST) anomalies in the Pacific and Atlantic Ocean and seasonal streamflow in the Midwestern U.S. Average Pacific and Atlantic Ocean SST anomalies, were calculated for 2 different 3 month series: September-November and December-February so as to create a lead time varying from 3 to 9 months. Streamflow were averaged for three seasons: spring (April-June), spring-summer (April-August) and summer (June-August). The correlation between streamflow and SST is analyzed using singular value decomposition for a period of 1960-2013. The result of the study showed several regions-other than the known Pacific and Atlantic Ocean regions- that were significantly correlated with streamflow stations. Higher correlation between the climate indices and streamflow were observed as the lead time decreased. The identification of the associations between SST and streamflow and significant SST regions in the Pacific and Atlantic Ocean may enhance the skill of streamflow predictability and water management in the region.

HYDRORECESSION: A toolbox for streamflow recession analysis

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Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

Substantial proportion of global streamflow less than three months old

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Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.

2016-02-01

Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

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Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

Causes and impacts of the 2005 Amazon drought

International Nuclear Information System (INIS)

Zeng Ning; Yoon, Jin-Ho; Marengo, Jose A; Nobre, Carlos A; Subramaniam, Ajit; Mariotti, Annarita; Neelin, J David

2008-01-01

A rare drought in the Amazon culminated in 2005, leading to near record-low streamflows, small Amazon river plume, and greatly enhanced fire frequency. This episode was caused by the combination of 2002-03 El Nino and a dry spell in 2005 attributable to a warm subtropical North Atlantic Ocean. Analysis for 1979-2005 reveals that the Atlantic influence is comparable to the better-known Pacific linkage. While the Pacific influence is typically locked to the wet season, the 2005 Atlantic impact concentrated in the Amazon dry season when its hydroecosystem is most vulnerable. Such mechanisms may have wide-ranging implications for the future of the Amazon rainforest

Hydro-Climatic Data Network (HCDN) Streamflow Data Set, 1874-1988

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Slack, James Richard; Lumb, Alan M.; Landwehr, Jurate Maciunas

1993-01-01

The potential consequences of climate change to continental water resources are of great concern in the management of those resources. Critically important to society is what effect fluctuations in the prevailing climate may have on hydrologic conditions, such as the occurrence and magnitude of floods or droughts and the seasonal distribution of water supplies within a region. Records of streamflow that are unaffected by artificial diversions, storage, or other works of man in or on the natural stream channels or in the watershed can provide an account of hydrologic responses to fluctuations in climate. By examining such records given known past meteorologic conditions, we can better understand hydrologic responses to those conditions and anticipate the effects of postulated changes in current climate regimes. Furthermore, patterns in streamflow records can indicate when a change in the prevailing climate regime may have occurred in the past, even in the absence of concurrent meteorologic records. A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing climatic conditions, has been developed. This data set, called the Hydro-Climatic Data Network, or HCDN, consists of streamflow records for 1,659 sites throughout United States and its Territories. Records cumulatively span the period 1874 through 1988, inclusive, and represent a total of 73,231 water years of information. Development of the HCDN Data Set: Records for the HCDN were obtained through a comprehensive search of the extensive surface- water data holdings of the U.S. Geological Survey (USGS), which are contained in the USGS National Water Storage and Retrieval System (WATSTORE). All streamflow discharge records in WATSTORE through September 30, 1988, were examined for inclusion in the HCDN in accordance with strictly defined criteria of measurement accuracy and natural conditions. No reconstructed

Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes

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W. Wang

2005-01-01

Full Text Available Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average models for seasonal streamflow series. However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity effect, a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.

Multi-index time series monitoring of drought and fire effects on desert grasslands

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Villarreal, Miguel; Norman, Laura M.; Buckley, Steven; Wallace, Cynthia S.A.; Coe, Michelle A.

2016-01-01

The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

Climate, streamflow, and legacy effects on growth of riparian Populus angustifolia in the arid San Luis Valley, Colorado

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Andersen, Douglas

2016-01-01

Knowledge of the factors affecting the vigor of desert riparian trees is important for their conservation and management. I used multiple regression to assess effects of streamflow and climate (12–14 years of data) or climate alone (up to 60 years of data) on radial growth of clonal narrowleaf cottonwood (Populus angustifolia), a foundation species in the arid, Closed Basin portion of the San Luis Valley, Colorado. I collected increment cores from trees (14–90 cm DBH) at four sites along each of Sand and Deadman creeks (total N = 85), including both perennial and ephemeral reaches. Analyses on trees conditions was common. Models for trees farther from the channel or over a deep water table explained 23–71% of SGI variability, and 4 of 5 contained a streamflow variable. Analyses using solely climate variables over longer time periods explained 17–85% of SGI variability, and 10 of 12 included a variable indexing summer precipitation. Three large, abrupt shifts in recent decades from wet to dry conditions (indexed by a seasonal Palmer Drought Severity Index) coincided with dramatically reduced radial growth. Each shift was presumably associated with branch dieback that produced a legacy effect apparent in many SGI series: uncharacteristically low SGI in the year following the shift. My results suggest trees in locations distant from the active channel rely on the regional shallow unconfined aquifer, summer rainfall, or both to meet water demands. The landscape-level differences in the water supplies sustaining these trees imply variable effects from shifts in winter-versus monsoon-related precipitation, and from climate change versus streamflow or groundwater management.

A new index for identifying socioeconomic drought events under climate change over the East River basin in China

Science.gov (United States)

Shi, H.; Chen, J.; Wang, K.; Niu, J.

2017-12-01

Drought, which means severe water deficiencies, is a complex natural hazard that may have destructive damages on societal properties and lives. Generally, socioeconomic drought occurs when the water resources systems cannot meet the water demands due to a weather-related shortfall in water supply to societies. This paper aims to propose a new index (i.e., socioeconomic drought index (SEDI)) for identifying socioeconomic drought events on different levels (i.e., slight, moderate, severe and extreme) under climate change through considering the gap between water supply and demand. First, the minimum in-stream water requirement (MWR) is determined through comprehensively considering the requirements of water quality, ecology, navigation and water supply. Second, according to the monthly water deficit calculated as the monthly streamflow data minus the MWR, drought month can be identified. Third, according to the cumulative water deficit derived from the monthly water deficit, drought duration (i.e., the number of continuous drought months) can be detected. Fourth, the SEDI of each socioeconomic drought event can be calculated through integrating the impacts of the cumulative water deficit and drought duration. The study area is the East River basin in South China, and the impact of a multi-year reservoir (i.e., the Xinfengjiang Reservoir) on drought is also analyzed. For historical and future drought analysis, it is concluded that the proposed SEDI is feasible to identify socioeconomic drought events. The results show that a number of socioeconomic drought events (including some extreme ones) may occur during 2020-2099, and the appropriate reservoir operation can significantly ease such situation.

Hydrologic Conditions that Influence Streamflow Losses in a Karst Region of the Upper Peace River, Polk County, Florida

Science.gov (United States)

Metz, P.A.; Lewelling, B.R.

2009-01-01

The upper Peace River from Bartow to Fort Meade, Florida, is described as a groundwater recharge area, reflecting a reversal from historical groundwater discharge patterns that existed prior to the 1950s. The upper Peace River channel and floodplain are characterized by extensive karst development, with numerous fractures, crevasses, and sinks that have been eroded in the near-surface and underlying carbonate bedrock. With the reversal in groundwater head gradients, river water is lost to the underlying groundwater system through these karst features. An investigation was conducted to evaluate the hydrologic conditions that influence streamflow losses in the karst region of the upper Peace River. The upper Peace River is located in a basin that has been altered substantially by phosphate mining and increases in groundwater use. These alterations have changed groundwater flow patterns and caused streamflow declines through time. Hydrologic factors that have had the greatest influence on streamflow declines in the upper Peace River include the lowering of the potentiometric surfaces of the intermediate aquifer system and Upper Floridan aquifer beneath the riverbed elevation due to below-average rainfall (droughts), increases in groundwater use, and the presence of numerous karst features in the low-water channel and floodplain that enhance the loss of streamflow. Seepage runs conducted along the upper Peace River, from Bartow to Fort Meade, indicate that the greatest streamflow losses occurred along an approximate 2-mile section of the river beginning about 1 mile south of the Peace River at Bartow gaging station. Along the low-water and floodplain channel of this 2-mile section, there are about 10 prominent karst features that influence streamflow losses. Losses from the individual karst features ranged from 0.22 to 16 cubic feet per second based on measurements made between 2002 and 2007. The largest measured flow loss for all the karst features was about 50 cubic

Adjusted Streamflow and Storage 1928-1989 : with Listings of Historical Streamflow, Summation of Storage Change and Adjusted Streamflow : Columbia River and Coastal Basins.

Energy Technology Data Exchange (ETDEWEB)

A.G. Crook Company

1993-04-01

The development of irrigation projects since the 1830's and the construction of major dams and reservoirs since the early 1900's have altered substantially the natural streamflow regimen of the Columbia River and its tributaries. As development expanded a multipurpose approach to streamflow regulation evolved to provide flood control, irrigation, hydropower generation, navigation, recreation, water quality enhancement, fish and wildlife, and instream flow maintenance. The responsible agencies use computer programs to determine the effects of various alternative system regulations. This report describes the development of the streamflow data that these computer programs use.

Modeling multisite streamflow dependence with maximum entropy copula

Science.gov (United States)

Hao, Z.; Singh, V. P.

2013-10-01

Synthetic streamflows at different sites in a river basin are needed for planning, operation, and management of water resources projects. Modeling the temporal and spatial dependence structure of monthly streamflow at different sites is generally required. In this study, the maximum entropy copula method is proposed for multisite monthly streamflow simulation, in which the temporal and spatial dependence structure is imposed as constraints to derive the maximum entropy copula. The monthly streamflows at different sites are then generated by sampling from the conditional distribution. A case study for the generation of monthly streamflow at three sites in the Colorado River basin illustrates the application of the proposed method. Simulated streamflow from the maximum entropy copula is in satisfactory agreement with observed streamflow.

Contribution of human and climate change impacts to changes in streamflow of Canada.

Science.gov (United States)

Tan, Xuezhi; Gan, Thian Yew

2015-12-04

Climate change exerts great influence on streamflow by changing precipitation, temperature, snowpack and potential evapotranspiration (PET), while human activities in a watershed can directly alter the runoff production and indirectly through affecting climatic variables. However, to separate contribution of anthropogenic and natural drivers to observed changes in streamflow is non-trivial. Here we estimated the direct influence of human activities and climate change effect to changes of the mean annual streamflow (MAS) of 96 Canadian watersheds based on the elasticity of streamflow in relation to precipitation, PET and human impacts such as land use and cover change. Elasticities of streamflow for each watershed are analytically derived using the Budyko Framework. We found that climate change generally caused an increase in MAS, while human impacts generally a decrease in MAS and such impact tends to become more severe with time, even though there are exceptions. Higher proportions of human contribution, compared to that of climate change contribution, resulted in generally decreased streamflow of Canada observed in recent decades. Furthermore, if without contributions from retreating glaciers to streamflow, human impact would have resulted in a more severe decrease in Canadian streamflow.

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing in the Wind River Range, Wyoming

Science.gov (United States)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2010-01-01

MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.

Modeling the Effects of Drought Events on Forest Ecosystem Functioning Historically and Under Scenarios of Climate Change

Science.gov (United States)

Ren, J.; Hanan, E. J.; Kolden, C.; Abatzoglou, J. T.; Tague, C.; Liu, M.; Adam, J. C.

2017-12-01

Drought events have been increasing across the western United States in recent years. Many studies have shown that, in the context of climate change, droughts will continue to be stronger, more frequent, and prolonged in the future. However, the response of forest ecosystems to droughts, particularly multi-year droughts, is not well understood. The objectives of this study are to examine how drought events of varying characteristics (e.g. intensity, duration, frequency, etc.) have affected the functioning of forest ecosystems historically, and how changing drought characteristics (including multi-year droughts) may affect forest functioning in a future climate. We utilize the Regional Hydro-Ecological Simulation System (RHESSys) to simulate impacts of both historical droughts and scenarios of future droughts on forest ecosystems. RHESSys is a spatially-distributed and process-based model that captures the interactions between coupled biogeochemical and hydrologic cycles at catchment scales. Here our case study is the Trail Creek catchment of the Big Wood River basin in Idaho, the Northwestern USA. For historical simulations, we use the gridded meteorological data of 1979 to 2016; for future climate scenarios, we utilize downscaled data from GCMs that have been demonstrated to capture drought events in the Northwest of the USA. From these climate projections, we identify various types of drought in intensity and duration, including multi-year drought events. We evaluate the following responses of ecosystems to these events: 1) evapotranspiration and streamflow; 2) gross primary productivity; 3) the post-drought recovery of plant biomass; and 4) the forest functioning and recovery after multi-year droughts. This research is part of an integration project to examine the roles of drought, insect outbreak, and forest management activities on wildfire activity and its impacts. This project will provide improved information for forest managers and communities in the wild

Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

Science.gov (United States)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-04-01

Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping

STREAMFLOW AND WATER QUALITY REGRESSION MODELING ...

African Journals Online (AJOL)

... downstream Obigbo station show: consistent time-trends in degree of contamination; linear and non-linear relationships for water quality models against total dissolved solids (TDS), total suspended sediment (TSS), chloride, pH and sulphate; and non-linear relationship for streamflow and water quality transport models.

Testing for Stationarity and Nonlinearity of Daily Streamflow Time Series Based on Different Statistical Tests (Case Study: Upstream Basin Rivers of Zarrineh Roud Dam

Directory of Open Access Journals (Sweden)

Farshad Fathian

2017-02-01

Full Text Available Introduction: Time series models are one of the most important tools for investigating and modeling hydrological processes in order to solve problems related to water resources management. Many hydrological time series shows nonstationary and nonlinear behaviors. One of the important hydrological modeling tasks is determining the existence of nonstationarity and the way through which we can access the stationarity accordingly. On the other hand, streamflow processes are usually considered as nonlinear mechanisms while in many studies linear time series models are used to model streamflow time series. However, it is not clear what kind of nonlinearity is acting underlying the streamflowprocesses and how intensive it is. Materials and Methods: Streamflow time series of 6 hydro-gauge stations located in the upstream basin rivers of ZarrinehRoud dam (located in the southern part of Urmia Lake basin have been considered to investigate stationarity and nonlinearity. All data series used here to startfrom January 1, 1997, and end on December 31, 2011. In this study, stationarity is tested by ADF and KPSS tests and nonlinearity is tested by BDS, Keenan and TLRT tests. The stationarity test is carried out with two methods. Thefirst one method is the augmented Dickey-Fuller (ADF unit root test first proposed by Dickey and Fuller (1979 and modified by Said and Dickey (1984, which examinsthe presence of unit roots in time series.The second onemethod is KPSS test, proposed by Kwiatkowski et al. (1992, which examinesthestationarity around a deterministic trend (trend stationarity and the stationarity around a fixed level (level stationarity. The BDS test (Brock et al., 1996 is a nonparametric method for testing the serial independence and nonlinear structure in time series based on the correlation integral of the series. The null hypothesis is the time series sample comes from an independent identically distributed (i.i.d. process. The alternative hypothesis

Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in Montana StreamStats

Science.gov (United States)

McCarthy, Peter M.

2016-04-05

Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.

Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI)

NARCIS (Netherlands)

Van Hoek, Mattijn; Jia, Li; Zhou, J.; Zheng, Chaolei; Menenti, M.

2016-01-01

The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation)

Impact of Different Time Series Streamflow Data on Energy Generation of a Run-of-River Hydropower Plant

Science.gov (United States)

Kentel, E.; Cetinkaya, M. A.

2013-12-01

Global issues such as population increase, power supply crises, oil prices, social and environmental concerns have been forcing countries to search for alternative energy sources such as renewable energy to satisfy the sustainable development goals. Hydropower is the most common form of renewable energy in the world. Hydropower does not require any fuel, produces relatively less pollution and waste and it is a reliable energy source with relatively low operating cost. In order to estimate the average annual energy production of a hydropower plant, sufficient and dependable streamflow data is required. The goal of this study is to investigate impact of streamflow data on annual energy generation of Balkusan HEPP which is a small run-of-river hydropower plant at Karaman, Turkey. Two different stream gaging stations are located in the vicinity of Balkusan HEPP and these two stations have different observation periods: one from 1986 to 2004 and the other from 2000 to 2009. These two observation periods show different climatic characteristics. Thus, annual energy estimations based on data from these two different stations differ considerably. Additionally, neither of these stations is located at the power plant axis, thus streamflow observations from these two stream gaging stations need to be transferred to the plant axis. This requirement introduces further errors into energy estimations. Impact of different streamflow data and transfer of streamflow observations to plant axis on annual energy generation of a small hydropower plant is investigated in this study.

Predictability of soil moisture and streamflow on subseasonal timescales: A case study

Science.gov (United States)

Orth, Rene; Seneviratne, Sonia I.

2013-10-01

Hydrological forecasts constitute an important tool in water resource management, especially in the case of impending extreme events. This study investigates the potential predictability of soil moisture and streamflow in Switzerland using a conceptual model including a simple water balance representation and a snow module. Our results show that simulated soil moisture and streamflow are more predictable (as indicated by significantly improved performance compared to climatology) until lead times of approximately 1 week and 2-3 days, respectively, when using initial soil moisture information and climatological atmospheric forcing. Using also initial snow information and seasonal weather forecasts as forcing, the predictable lead time doubles in case of soil moisture and triples for streamflow. The skill contributions of the additional information vary with altitude; at low altitudes the precipitation forecast is most important, whereas in mountainous areas the temperature forecast and the initial snow information are the most valuable contributors. We find furthermore that the soil moisture and streamflow forecast skills increase with increasing initial soil moisture anomalies. Comparing the respective value of realistic initial conditions and state-of-the-art forcing forecasts, we show that the former are generally more important for soil moisture forecasts, whereas the latter are more valuable for streamflow forecasts. To relate the derived predictabilities to respective soil moisture and streamflow memories investigated in other publications, we additionally illustrate the similarity between the concepts of memory and predictability as measures of persistence in the last part of this study.

Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

Directory of Open Access Journals (Sweden)

S. A. Archfield

2013-01-01

Full Text Available Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.

Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

Science.gov (United States)

Archfield, Stacey A.; Steeves, Peter A.; Guthrie, John D.; Ries, Kernell G.

2013-01-01

Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.

On the sensitivity of annual streamflow to air temperature

Science.gov (United States)

Milly, Paul C.D.; Kam, Jonghun; Dunne, Krista A.

2018-01-01

Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.

Proteomic responses of drought-tolerant and drought-sensitive cotton varieties to drought stress.

Science.gov (United States)

Zhang, Haiyan; Ni, Zhiyong; Chen, Quanjia; Guo, Zhongjun; Gao, Wenwei; Su, Xiujuan; Qu, Yanying

2016-06-01

Drought, one of the most widespread factors reducing agricultural crop productivity, affects biological processes such as development, architecture, flowering and senescence. Although protein analysis techniques and genome sequencing have made facilitated the proteomic study of cotton, information on genetic differences associated with proteomic changes in response to drought between different cotton genotypes is lacking. To determine the effects of drought stress on cotton seedlings, we used two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry to comparatively analyze proteome of drought-responsive proteins during the seedling stage in two cotton (Gossypium hirsutum L.) cultivars, drought-tolerant KK1543 and drought-sensitive Xinluzao26. A total of 110 protein spots were detected on 2-DE maps, of which 56 were identified by MALDI-TOF and MALDI-TOF/TOF mass spectrometry. The identified proteins were mainly associated with metabolism (46.4 %), antioxidants (14.2 %), and transport and cellular structure (23.2 %). Some key proteins had significantly different expression patterns between the two genotypes. In particular, 5-methyltetrahydropteroyltriglutamate-homocysteine methyltransferase, UDP-D-glucose pyrophosphorylase and ascorbate peroxidase were up-regulated in KK1543 compared with Xinluzao26. Under drought stress conditions, the vacuolar H(+)-ATPase catalytic subunit, a 14-3-3g protein, translation initiation factor 5A and pathogenesis-related protein 10 were up-regulated in KK1543, whereas ribosomal protein S12, actin, cytosolic copper/zinc superoxide dismutase, protein disulfide isomerase, S-adenosylmethionine synthase and cysteine synthase were down-regulated in Xinluzao26. This work represents the first characterization of proteomic changes that occur in response to drought in roots of cotton plants. These differentially expressed proteins may be related to

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

Science.gov (United States)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

Towards a Seamless Framework for Drought Analysis and Prediction from Seasonal to Climate Change Time Scales (Plinius Medal Lecture)

Science.gov (United States)

Sheffield, Justin

2013-04-01

Droughts arguably cause the most impacts of all natural hazards in terms of the number of people affected and the long-term economic costs and ecosystem stresses. Recent droughts worldwide have caused humanitarian and economic problems such as food insecurity across the Horn of Africa, agricultural economic losses across the central US and loss of livelihoods in rural western India. The prospect of future increases in drought severity and duration driven by projected changes in precipitation patterns and increasing temperatures is worrisome. Some evidence for climate change impacts on drought is already being seen for some regions, such as the Mediterranean and east Africa. Mitigation of the impacts of drought requires advance warning of developing conditions and enactment of drought plans to reduce vulnerability. A key element of this is a drought early warning system that at its heart is the capability to monitor evolving hydrological conditions and water resources storage, and provide reliable and robust predictions out to several months, as well as the capacity to act on this information. At longer time scales, planning and policy-making need to consider the potential impacts of climate change and its impact on drought risk, and do this within the context of natural climate variability, which is likely to dominate any climate change signal over the next few decades. There are several challenges that need to be met to advance our capability to provide both early warning at seasonal time scales and risk assessment under climate change, regionally and globally. Advancing our understanding of drought predictability and risk requires knowledge of drought at all time scales. This includes understanding of past drought occurrence, from the paleoclimate record to the recent past, and understanding of drought mechanisms, from initiation, through persistence to recovery and translation of this understanding to predictive models. Current approaches to monitoring and

Climate and Streamflow Reconstruction on the São Francisco Basin, Brazil, Using Tree-Ring Data

Science.gov (United States)

Pereira, G. D. A.; Barbosa, A. C. M. C.; Granato-Souza, D.; Stahle, D. W.; Torbenson, M.; dos Santos, R. M.; Rodrigues Alves Delfino Barbosa, J. P.

2017-12-01

The São Francisco River crosses the most drought-prone region of Brazil and regional economic dynamics are dependent on the water availability in the basin. The seasonally dry forests are widely distributed in the basin, where Cedrela fissilis Vell (cedro) are frequently found. This semi-arid region provides a favorable setting where the deciduous cedro trees form well-defined semi-ring porous annual rings that can be exactly crossdated and used to build climate sensitive chronologies. Therefore, we have developed chronologies of cedro from seasonally dry forest fragments of three sites located in the middle-sector of the São Francisco River basin and south limit of the Brazilian Drought Polygon. The samples were analyzed according to standard procedures: sample preparation, ring count, crossdating and measurement of the tree rings. Dating quality was tested using the computer program COFECHA and ring-width time series where detrended and standardized to produce the final index chronology using the ARSTAN program. The results show that crossdating within and among trees from different sites demonstrate the potential to expand the spatial sampling. The tree-ring chronologies are sensitive with wet season precipitation totals (October - March), and can explain approximately 40% of the variance (1961-2015). Significant correlation was also observed with total annual discharge of the Rio São Francisco River measured at Barra (r=0.48; 1961-2015). However, the correlation disapears after 1993 (r=0.64 for 1961-1993, but r=-0.004 for 1994-2015) and we suspect that the stream gage at Barra has been impacted by human activity. Tree-ring chronologies can provide important information on climate and streamflow variability of São Francisco River, where hydrological records are often short and discontinuous. This chronology is now being extended with 150-yr old trees from the region and may be used to reconstruct climate and streamflow records back to the pre

In Brief: Online database for instantaneous streamflow data

Science.gov (United States)

Showstack, Randy

2007-11-01

Access to U.S. Geological Survey (USGS) historical instantaneous streamflow discharge data, dating from around 1990, is now available online through the Instantaneous Data Archive (IDA), the USGS announced on 14 November. In this new system, users can find streamflow information reported at the time intervals at which it is collected, typically 15-minute to hourly intervals. Although instantaneous data have been available for many years, they were not accessible through the Internet. Robert Hirsch, USGS Associate Director of Water, said, ``A user-friendly archive of historical instantaneous streamflow data is important to many different users for such things as floodplain mapping, flood modeling, and estimating pollutant transport.''The site currently has about 1.5 billion instantaneous data values from 5500 stream gages in 26 states. The number of states and stream gages with data will continue to increase, according to the USGS. For more information, visit the Web site: http://ida.water.usgs.gov/ida/.

Preliminary assessment of streamflow characteristics for selected streams at Fort Gordon, Georgia, 1999-2000

Science.gov (United States)

Stamey, Timothy C.

2001-01-01

In 1999, the U.S. Geological Survey, in cooperation with the U.S. Army Signal Center and Fort Gordon, began collection of periodic streamflow data at four streams on the military base to assess and estimate streamflow characteristics of those streams for potential water-supply sources. Simple and reliable methods of determining streamflow characteristics of selected streams on the military base are needed for the initial implementation of the Fort Gordon Integrated Natural Resources Management Plan. Long-term streamflow data from the Butler Creek streamflow gaging station were used along with several concurrent discharge measurements made at three selected partial-record streamflow stations on Fort Gordon to determine selected low-flow streamflow characteristics. Streamflow data were collected and analyzed using standard U.S. Geological Survey methods and computer application programs to verify the use of simple drainage area to discharge ratios, which were used to estimate the low-flow characteristics for the selected streams. Low-flow data computed based on daily mean streamflow include: mean discharges for consecutive 1-, 3-, 7-, 14-, and 30-day period and low-flow estimates of 7Q10, 30Q2, 60Q2, and 90Q2 recurrence intervals. Flow-duration data also were determined for the 10-, 30-, 50-, 70-, and 90-percent exceedence flows. Preliminary analyses of the streamflow indicate that the flow duration and selected low-flow statistics for the selected streams averages from about 0.15 to 2.27 cubic feet per square mile. The long-term gaged streamflow data indicate that the streamflow conditions for the period analyzed were in the 50- to 90-percent flow range, or in which streamflow would be exceeded about 50 to 90 percent of the time.

Data Pre-Analysis and Ensemble of Various Artificial Neural Networks for Monthly Streamflow Forecasting

Directory of Open Access Journals (Sweden)

Jianzhong Zhou

2018-05-01

Full Text Available This paper introduces three artificial neural network (ANN architectures for monthly streamflow forecasting: a radial basis function network, an extreme learning machine, and the Elman network. Three ensemble techniques, a simple average ensemble, a weighted average ensemble, and an ANN-based ensemble, were used to combine the outputs of the individual ANN models. The objective was to highlight the performance of the general regression neural network-based ensemble technique (GNE through an improvement of monthly streamflow forecasting accuracy. Before the construction of an ANN model, data preanalysis techniques, such as empirical wavelet transform (EWT, were exploited to eliminate the oscillations of the streamflow series. Additionally, a theory of chaos phase space reconstruction was used to select the most relevant and important input variables for forecasting. The proposed GNE ensemble model has been applied for the mean monthly streamflow observation data from the Wudongde hydrological station in the Jinsha River Basin, China. Comparisons and analysis of this study have demonstrated that the denoised streamflow time series was less disordered and unsystematic than was suggested by the original time series according to chaos theory. Thus, EWT can be adopted as an effective data preanalysis technique for the prediction of monthly streamflow. Concurrently, the GNE performed better when compared with other ensemble techniques.

Climate change streamflow scenarios designed for critical period water resources planning studies

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Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the

Moving Beyond Streamflow Observations: Lessons From A Multi-Objective Calibration Experiment in the Mississippi Basin

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Koppa, A.; Gebremichael, M.; Yeh, W. W. G.

2017-12-01

Calibrating hydrologic models in large catchments using a sparse network of streamflow gauges adversely affects the spatial and temporal accuracy of other water balance components which are important for climate-change, land-use and drought studies. This study combines remote sensing data and the concept of Pareto-Optimality to address the following questions: 1) What is the impact of streamflow (SF) calibration on the spatio-temporal accuracy of Evapotranspiration (ET), near-surface Soil Moisture (SM) and Total Water Storage (TWS)? 2) What is the best combination of fluxes that can be used to calibrate complex hydrological models such that both the accuracy of streamflow and the spatio-temporal accuracy of ET, SM and TWS is preserved? The study area is the Mississippi Basin in the United States (encompassing HUC-2 regions 5,6,7,9,10 and 11). 2003 and 2004, two climatologically average years are chosen for calibration and validation of the Noah-MP hydrologic model. Remotely sensed ET data is sourced from GLEAM, SM from ESA-CCI and TWS from GRACE. Single objective calibration is carried out using DDS Algorithm. For Multi objective calibration PA-DDS is used. First, the Noah-MP model is calibrated using a single objective function (Minimize Mean Square Error) for the outflow from the 6 HUC-2 sub-basins for 2003. Spatial correlograms are used to compare the spatial structure of ET, SM and TWS between the model and the remote sensing data. Spatial maps of RMSE and Mean Error are used to quantify the impact of calibrating streamflow on the accuracy of ET, SM and TWS estimates. Next, a multi-objective calibration experiment is setup to determine the pareto optimal parameter sets (pareto front) for the following cases - 1) SF and ET, 2) SF and SM, 3) SF and TWS, 4) SF, ET and SM, 5) SF, ET and TWS, 6) SF, SM and TWS, 7) SF, ET, SM and TWS. The best combination of fluxes that provides the optimal trade-off between accurate streamflow and preserving the spatio

A field study in the Swiss Rietholzbach basin to understand landscape filtering of hydro-climatic drivers and its effects on streamflow composition

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von Freyberg, J.; Schirmer, M.

2013-12-01

Non-linear hydrological behavior of small mountainous watersheds is often attributed to variable streamflow contributions from different landscape units that differ in subsurface properties, vegetation cover and land use. Within this concept, the role of landscape can be seen as that of a filter, translating hydro-climatic drivers into particular streamflow signals - such as discharge rates or water quality. Our research addresses the question of how hydrologic connectivity between the relevant landscape units evolves during storm events and droughts at headwater catchments and seeks to establish a general framework of interdisciplinary interest (e.g., ecology and climate science). We focus on the description of groundwater flow on the local and regional scale, since groundwater - surface water - interaction in the valley bottoms, transport mechanisms of nutrients within hyporheic zones, and groundwater flow dynamics in the shallow subsurface have all been identified as important processes in describing hydrologic catchment response and streamflow composition. Our field-based study takes place in the pre-Alpine Rietholzbach research catchment (~ 3 sq km) in the headwaters of the Thur basin in NE Switzerland. We investigated the effects of landscape properties on river water quality and catchment hydrology over a two-year period. The Rietholzbach research catchment is equipped with a meteorological station, a weighting lysimeter, 20 piezometers, 3 stream gauging stations and various soil moisture and temperature probes, which provide continuous, high-frequency measurements of atmospheric and hydrometric data. These measurements are used in combination with hydro-chemistry data to determine groundwater residence times and streamflow composition. The installed setup facilitates the investigation of annual, inter-seasonal as well as short-term dynamics of water flow and its links to associated parameters describing atmospheric, surface and subsurface properties. We

Trends in precipitation and streamflow and changes in stream morphology in the Fountain Creek watershed, Colorado, 1939-99

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Stogner, Sr., Robert W.

2000-01-01

The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of

Ecological drought: Accounting for the non-human impacts of water shortage in the Upper Missouri Headwaters Basin, Montana, USA

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McEvoy, Jamie; Bathke, Deborah J.; Burkardt, Nina; Cravens, Amanda; Haigh, Tonya; Hall, Kimberly R.; Hayes, Michael J.; Jedd, Theresa; Podebradska, Marketa; Wickham, Elliot

2018-01-01

Water laws and drought plans are used to prioritize and allocate scarce water resources. Both have historically been human-centric, failing to account for non-human water needs. In this paper, we examine the development of instream flow legislation and the evolution of drought planning to highlight the growing concern for the non-human impacts of water scarcity. Utilizing a new framework for ecological drought, we analyzed five watershed-scale drought plans in southwestern Montana, USA to understand if, and how, the ecological impacts of drought are currently being assessed. We found that while these plans do account for some ecological impacts, it is primarily through the narrow lens of impacts to fish as measured by water temperature and streamflow. The latter is typically based on the same ecological principles used to determine instream flow requirements. We also found that other resource plans in the same watersheds (e.g., Watershed Restoration Plans, Bureau of Land Management (BLM) Watershed Assessments or United States Forest Service (USFS) Forest Plans) identify a broader range of ecological drought risks. Given limited resources and the potential for mutual benefits and synergies, we suggest greater integration between various planning processes could result in a more holistic consideration of water needs and uses across the landscape.

Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

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Paul, M.; Negahban-Azar, M.

2017-12-01

The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

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Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008

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Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall

2012-01-01

Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios

Populus species from diverse habitats maintain high night-time conductance under drought.

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Cirelli, Damián; Equiza, María Alejandra; Lieffers, Victor James; Tyree, Melvin Thomas

2016-02-01

We investigated the interspecific variability in nocturnal whole-plant stomatal conductance under well-watered and drought conditions in seedlings of four species of Populus from habitats characterized by abundant water supply (mesic and riparian) or from drier upland sites. The study was carried out to determine whether (i) nocturnal conductance varies across different species of Populus according to their natural habitat, (ii) nocturnal conductance is affected by water stress similarly to daytime conductance based on species habitat and (iii) differences in conductance among species could be explained partly by differences in stomatal traits. We measured whole-plant transpiration and conductance (G) of greenhouse-grown seedlings using an automated high-resolution gravimetric technique. No relationship was found between habitat preference and daytime G (GD), but night-time G (GN) was on average 1.5 times higher in riparian and mesic species (P. deltoides Bartr. ex Marsh. and P. trichocarpa Torr. & Gray) than in those from drier environments (P. tremuloides Michx. and P. × petrowskyana Schr.). GN was not significantly reduced under drought in riparian species. Upland species restricted GN significantly in response to drought, but it was still at least one order of magnitude greater that the cuticular conductance until leaf death was imminent. Under both well-watered and drought conditions, GN declined with increasing vapour pressure deficit (D). Also, a small increase in GN towards the end of the night period was observed in P. deltoides and P. × petrowskyana, suggesting the involvement of endogenous regulation. The anatomical analyses indicated a positive correlation between G and variable stomatal pore index among species and revealed that stomata are not likely to be leaky but instead seem capable of complete occlusion, which raises the question of the possible physiological role of the significant GN observed under drought. Further comparisons among

Streamflow disaggregation: a nonlinear deterministic approach

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B. Sivakumar

2004-01-01

Full Text Available This study introduces a nonlinear deterministic approach for streamflow disaggregation. According to this approach, the streamflow transformation process from one scale to another is treated as a nonlinear deterministic process, rather than a stochastic process as generally assumed. The approach follows two important steps: (1 reconstruction of the scalar (streamflow series in a multi-dimensional phase-space for representing the transformation dynamics; and (2 use of a local approximation (nearest neighbor method for disaggregation. The approach is employed for streamflow disaggregation in the Mississippi River basin, USA. Data of successively doubled resolutions between daily and 16 days (i.e. daily, 2-day, 4-day, 8-day, and 16-day are studied, and disaggregations are attempted only between successive resolutions (i.e. 2-day to daily, 4-day to 2-day, 8-day to 4-day, and 16-day to 8-day. Comparisons between the disaggregated values and the actual values reveal excellent agreements for all the cases studied, indicating the suitability of the approach for streamflow disaggregation. A further insight into the results reveals that the best results are, in general, achieved for low embedding dimensions (2 or 3 and small number of neighbors (less than 50, suggesting possible presence of nonlinear determinism in the underlying transformation process. A decrease in accuracy with increasing disaggregation scale is also observed, a possible implication of the existence of a scaling regime in streamflow.

Investigating runoff efficiency in upper Colorado River streamflow over past centuries

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Woodhouse, Connie A.; Pederson, Gregory T.

2018-01-01

With increasing concerns about the impact of warming temperatures on water resources, more attention is being paid to the relationship between runoff and precipitation, or runoff efficiency. Temperature is a key influence on Colorado River runoff efficiency, and warming temperatures are projected to reduce runoff efficiency. Here, we investigate the nature of runoff efficiency in the upper Colorado River (UCRB) basin over the past 400 years, with a specific focus on major droughts and pluvials, and to contextualize the instrumental period. We first verify the feasibility of reconstructing runoff efficiency from tree-ring data. The reconstruction is then used to evaluate variability in runoff efficiency over periods of high and low flow, and its correspondence to a reconstruction of late runoff season UCRB temperature variability. Results indicate that runoff efficiency has played a consistent role in modulating the relationship between precipitation and streamflow over past centuries, and that temperature has likely been the key control. While negative runoff efficiency is most common during dry periods, and positive runoff efficiency during wet years, there are some instances of positive runoff efficiency moderating the impact of precipitation deficits on streamflow. Compared to past centuries, the 20th century has experienced twice as many high flow years with negative runoff efficiency, likely due to warm temperatures. These results suggest warming temperatures will continue to reduce runoff efficiency in wet or dry years, and that future flows will be less than anticipated from precipitation due to warming temperatures.

Anatomy of Human Interventions on the Alteration of Drought Risk over the Conterminous US

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He, X.; Wada, Y.; Wanders, N.; Sheffield, J.

2017-12-01

Drought attribution focusing on anthropogenic climate change has received wide attentions. However, human interventions (HIs), such as irrigation, reservoir operation, and water use, are less well known. In this study, using the large-scale water resources model PCR-GLOBWB, we perform a suite of high-resolution ( 10 km) simulations over the conterminous US (CONUS) in order to disentangle the fingerprints of individual HI elements on changes of hydrological drought. The results show significant trend differences between scenarios with and without HIs in certain regions of the CONUS. HIs cause increased trends in drought severity for the High Plains, California and Mid-Atlantic region, whereas decreased trend emerges in the California Central Valley, lower Mississippi basin and Pacific Northwest. The mechanism of altered drought severity can be broken down into three individual parts, with irrigation increasing the trend in the High Plains and Central Valley, reservoir operation decreasing the trend in Western US and water use amplifying the trend in the urban areas. Besides the trend analysis, we show the relative contribution of water abstraction and return flows to explain how each HI contributes to enhancing or mitigating drought. Results demonstrate that return flows from agricultural irrigation increase recharge and therefore can alleviate hydrological drought (e.g., by 60-80% in Mississippi embayment). Further examination of the water sources indicates that in these drought alleviation hotspots, non-fossil groundwater dominates the total water abstraction. However, for the hotspots of drought intensification (e.g., southern High Plains), extensive irrigational pumping causes severe depletion of fossil groundwater, which reduces the interaction between baseflow and channel flow, and therefore reduces the total streamflow. Return level analysis is further applied to quantify how different types of HIs could alter the probability of occurrence of recent major

Detecting Drought-Induced Tree Mortality in Sierra Nevada Forests with Time Series of Satellite Data

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Sarah Byer

2017-09-01

Full Text Available A five-year drought in California led to a significant increase in tree mortality in the Sierra Nevada forests from 2012 to 2016. Landscape level monitoring of forest health and tree dieback is critical for vegetation and disaster management strategies. We examined the capability of multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS in detecting and explaining the impacts of the recent severe drought in Sierra Nevada forests. Remote sensing metrics were developed to represent baseline forest health conditions and drought stress using time series of MODIS vegetation indices (VIs and a water index. We used Random Forest algorithms, trained with forest aerial detection surveys data, to detect tree mortality based on the remote sensing metrics and topographical variables. Map estimates of tree mortality demonstrated that our two-stage Random Forest models were capable of detecting the spatial patterns and severity of tree mortality, with an overall producer’s accuracy of 96.3% for the classification Random Forest (CRF and a RMSE of 7.19 dead trees per acre for the regression Random Forest (RRF. The overall omission errors of the CRF ranged from 19% for the severe mortality class to 27% for the low mortality class. Interpretations of the models revealed that forests with higher productivity preceding the onset of drought were more vulnerable to drought stress and, consequently, more likely to experience tree mortality. This method highlights the importance of incorporating baseline forest health data and measurements of drought stress in understanding forest response to severe drought.

Reconstruction and analysis of the past five centuries of streamflow on northern slopes on Tianshan Mountains in Northern Xinjiang, China

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Yang, Yuhui; Chen, Yaning; Wang, Minzhong; Sun, Huilan

2017-07-01

We examined the changes in streamflow on the northern slopes of the Tianshan Mountains in northern Xinjiang, China, over two time scales: the past 500 years, based on dendrochronology data; and the past 50 years, based on streamflow data from hydrological stations. The method of artificial neural networks built from the data of the 50-year period was used to reconstruct the streamflow of the 500-year period. The results indicate that streamflow has undergone seven high-flow periods and four low-flow periods during the past 500 years. To identify possible transition points in the streamflow, we applied the Mann-Kendall and running T tests to the 50- and 500-year periods, respectively. During the past 500 years, streamflow has changed significantly from low to high flow about three to four times, and from high to low flow about three to five times. Over the recent 50 years, there have been three phases of variation in river runoff, and the most distinct transition of streamflow occurred in 1996.

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

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Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin

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Vibhava, F.; Graham, W. D.; Maxwell, R. M.

2012-12-01

Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

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Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

2015-08-24

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Drought assessment in the Dongliao River basin: traditional approaches vs. generalized drought assessment index based on water resources systems

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Weng, B. S.; Yan, D. H.; Wang, H.; Liu, J. H.; Yang, Z. Y.; Qin, T. L.; Yin, J.

2015-08-01

Drought is firstly a resource issue, and with its development it evolves into a disaster issue. Drought events usually occur in a determinate but a random manner. Drought has become one of the major factors to affect sustainable socioeconomic development. In this paper, we propose the generalized drought assessment index (GDAI) based on water resources systems for assessing drought events. The GDAI considers water supply and water demand using a distributed hydrological model. We demonstrate the use of the proposed index in the Dongliao River basin in northeastern China. The results simulated by the GDAI are compared to observed drought disaster records in the Dongliao River basin. In addition, the temporal distribution of drought events and the spatial distribution of drought frequency from the GDAI are compared with the traditional approaches in general (i.e., standard precipitation index, Palmer drought severity index and rate of water deficit index). Then, generalized drought times, generalized drought duration, and generalized drought severity were calculated by theory of runs. Application of said runs at various drought levels (i.e., mild drought, moderate drought, severe drought, and extreme drought) during the period 1960-2010 shows that the centers of gravity of them all distribute in the middle reaches of Dongliao River basin, and change with time. The proposed methodology may help water managers in water-stressed regions to quantify the impact of drought, and consequently, to make decisions for coping with drought.

Performing drought indices to identify the relationship between agricultural losses and drought events in Spain.

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Peña Gallardo, Marina; Serrano, Sergio Martín Vicente; Portugués Santiago, Beguería; Burguera Miquel, Tomás

2017-04-01

Drought leads to crop failures reducing the productivity. For this reason, the need of appropriate tool for recognize dry periods and evaluate the impact of drought on crop production is important. In this study, we provide an assessment of the relationship between drought episodes and crop failures in Spain as one of the direct consequences of drought is the diminishing of crop yields. First, different drought indices [the Standardized Precipitation and Evapotranspiration Index (SPEI); the Standardized Precipitation Index (SPI); the self-calibrated Palmer Moisture Anomaly Index (Z-Index), the self-calibrated Crop Moisture Index (CMI) and the Standardized Palmer Drought Index (SPDI)] have been calculated at different time scales in order to identify the dry events occurred in Spain and determine the duration and intensity of each event. Second, the drought episodes have been correlated with crop production estimated and final crop production data provided by the Spanish Crop Insurance System for the available period from 1995 to 2014 at the municipal spatial scale, with the purpose of knowing if the characteristics of the drought episodes are reflected on the agricultural losses. The analysis has been carried out in particular for two types of crop, wheat and barley. The results indicate the existence of an agreement between the most important drought events in Spain and the response of the crop productions and the proportion of hectare insurance. Nevertheless, this agreement vary depending on the drought index applied. Authors found a higher competence of the drought indices calculated at different time scales (SPEI, SPI and SPDI) identifying the begging and end of the drought events and the correspondence with the crop failures.

Groundwater Depletion During Drought Threatens Future Water Security of the Colorado River Basin

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Castle, Stephanie L.; Thomas, Brian F.; Reager, John T.; Rodell, Matthew; Swenson, Sean C.; Famiglietti, James S.

2014-01-01

Streamflow of the Colorado River Basin is the most overallocated in the world. Recent assessment indicates that demand for this renewable resource will soon outstrip supply, suggesting that limited groundwater reserves will play an increasingly important role in meeting future water needs. Here we analyze 9 years (December 2004 to November 2013) of observations from the NASA Gravity Recovery and Climate Experiment mission and find that during this period of sustained drought, groundwater accounted for 50.1 cu km of the total 64.8 cu km of freshwater loss. The rapid rate of depletion of groundwater storage (5.6 +/- 0.4 cu km/yr) far exceeded the rate of depletion of Lake Powell and Lake Mead. Results indicate that groundwater may comprise a far greater fraction of Basin water use than previously recognized, in particular during drought, and that its disappearance may threaten the long-term ability to meet future allocations to the seven Basin states.

Analysis of trends in selected streamflow statistics for the Concho River Basin, Texas, 1916-2009

Science.gov (United States)

Barbie, Dana L.; Wehmeyer, Loren L.; May, Jayne E.

2012-01-01

The Concho River Basin is part of the upper Colorado River Basin in west-central Texas. Monotonic trends in streamflow statistics during various time intervals from 1916-2009 were analyzed to determine whether substantial changes in selected streamflow statistics have occurred within the Concho River Basin. Two types of U.S. Geological Survey streamflow data comprise the foundational data for this report: (1) daily mean discharge (daily discharge) and (2) annual instantaneous peak discharge. Trend directions are reported for the following streamflow statistics: (1) annual mean daily discharge, (2) annual 1-day minimum discharge, (3) annual 7-day minimum discharge, (4) annual maximum daily discharge, and (5) annual instantaneous peak discharge.

Multidecadal change in streamflow associated with anthropogenic disturbances in the tropical Andes

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Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.

2015-10-01

Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974-2008) and land cover reconstructions (1963-2009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963-2009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or -31 km2) corresponding to a mean rate of 67 ha yr-1, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963-2009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.

Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

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Van Loon, Anne F.; Stahl, Kerstin; Di Baldassarre, Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko; Gleeson, Tom; Van Dijk, Albert I. J. M.; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Adriaan J.; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; Wagener, Thorsten; Van Lanen, Henny A. J.

2016-09-01

are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future.

Sensitivity of monthly streamflow forecasts to the quality of rainfall forcing: When do dynamical climate forecasts outperform the Ensemble Streamflow Prediction (ESP) method?

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Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.

2017-12-01

Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments

Disentangling the response of streamflow to forest management and climate

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Dymond, S.; Miniat, C.; Bladon, K. D.; Keppeler, E.; Caldwell, P. V.

2016-12-01

Paired watershed studies have showcased the relationships between forests, management, and streamflow. However, classical analyses of paired-watershed studies have done little to disentangle the effects of management from overarching climatic signals, potentially masking the interaction between management and climate. Such approaches may confound our understanding of how forest management impacts streamflow. Here we use a 50-year record of streamflow and climate data from the Caspar Creek Experimental Watersheds (CCEW), California, USA to separate the effects of forest management and climate on streamflow. CCEW has two treatment watersheds that have been harvested in the past 50 years. We used a nonlinear mixed model to combine the pre-treatment relationship between streamflow and climate and the post-treatment relationship via an interaction between climate and management into one equation. Our results show that precipitation and potential evapotranspiration alone can account for >95% of the variability in pre-treatment streamflow. Including management scenarios into the model explained most of the variability in streamflow (R2 > 0.98). While forest harvesting altered streamflow in both of our modeled watersheds, removing 66% of the vegetation via selection logging using a tractor yarding system over the entire watershed had a more substantial impact on streamflow than clearcutting small portions of a watershed using cable-yarding. These results suggest that forest harvesting may result in differing impacts on streamflow and highlights the need to incorporate climate into streamflow analyses of paired-watershed studies.

Gel-free/label-free proteomic analysis of root tip of soybean over time under flooding and drought stresses.

Science.gov (United States)

Wang, Xin; Oh, MyeongWon; Sakata, Katsumi; Komatsu, Setsuko

2016-01-01

Growth in the early stage of soybean is markedly inhibited under flooding and drought stresses. To explore the responsive mechanisms of soybean, temporal protein profiles of root tip under flooding and drought stresses were analyzed using gel-free/label-free proteomic technique. Root tip was analyzed because it was the most sensitive organ against flooding, and it was beneficial to root penetration under drought. UDP glucose: glycoprotein glucosyltransferase was decreased and increased in soybean root under flooding and drought, respectively. Temporal protein profiles indicated that fermentation and protein synthesis/degradation were essential in root tip under flooding and drought, respectively. In silico protein-protein interaction analysis revealed that the inductive and suppressive interactions between S-adenosylmethionine synthetase family protein and B-S glucosidase 44 under flooding and drought, respectively, which are related to carbohydrate metabolism. Furthermore, biotin/lipoyl attachment domain containing protein and Class II aminoacyl tRNA/biotin synthetases superfamily protein were repressed in the root tip during time-course stresses. These results suggest that biotin and biotinylation might be involved in energy management to cope with flooding and drought in early stage of soybean-root tip. Copyright © 2015 Elsevier B.V. All rights reserved.

Simulation of streamflow in the McTier Creek watershed, South Carolina

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Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.

2010-01-01

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient

On the probability distribution of daily streamflow in the United States

Science.gov (United States)

Blum, Annalise G.; Archfield, Stacey A.; Vogel, Richard M.

2017-06-01

Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.

Integrated approach to assessing streamflow and precipitation alterations under environmental change: Application in the Niger River Basin

Directory of Open Access Journals (Sweden)

Dagbegnon Clement Sohoulande Djebou

2015-09-01

New hydrological insights for the region: Over the period 1961–2012, I conduct a change point analysis of the streamflow and report two sub-periods 1961–1982 and 1983–2012. A comparison of precipitation and streamflow during these two time-slices shows meaningful changes. I describe a Kernel density analysis of streamflow and yield a probabilistic estimate of discharge anomalies along the river. Later, I evaluate seasonal trends of precipitation and streamflow. The analyses bring out critical alterations in time and space. However, these alterations seem to foreshadow critical environmental degradations occurring across the watershed. I consider LAI series derived from MODIS images, then I examine and discuss trends in land-cover dynamics in relation with the patterns in precipitation and streamflow. This late analytical step yields a holistic picture of the ongoing alterations in the Niger River Basin. Finally, I emphasize suggestions, valuable for a comprehensive water resources and environment management.

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions

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Lingfeng Duan

2018-04-01

Full Text Available Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR, perimeter area ratio (PAR and total plant area/convex hull area ratio (TCR]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals. We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional

Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia

International Nuclear Information System (INIS)

Tan, M L

2014-01-01

Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as ''input'' to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the ''goodness-of-fit'' between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy

Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia

Science.gov (United States)

Tan, M. L.

2014-02-01

Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.

Detecting the hydrological impacts of forest cover change in tropical mountain areas: need for detrending time series of rainfall and streamflow data.

Science.gov (United States)

Molina, A.; Vanacker, V.; Brisson, E.; Balthazar, V.

2012-04-01

Interactions between human activities and the physical environment have increasingly transformed the hydrological functioning of Andean ecosystems. In these human-modified landscapes, land use/-cover change may have a profound effect on riverine water and sediment fluxes. The hydrological impacts of land use/-cover change are diverse, as changes in vegetation affect the various components of the hydrological cycle including evapotranspiration, infiltration and surface runoff. Quantitative data for tropical mountain regions are scarce, as few long time series on rainfall, water discharge and land use are available. Furthermore, time series of rainfall and streamflow data in tropical mountains are often highly influenced by large inter- and intra-annual variability. In this paper, we analyse the hydrological response to complex forest cover change for a catchment of 280 km2 located in the Ecuadorian Andes. Forest cover change in the Pangor catchment was reconstructed based on airphotos (1963, 1977), LANDSAT TM (1991) and ETM+ data (2001, 2009). From 1963, natural vegetation was converted to agricultural land and pine plantations: forests decreased by a factor 2, and paramo decreased by 20 km2 between 1963 and 2009. For this catchment, there exists an exceptionally long record of rainfall and streamflow data that dates back from the '70s till now, but large variability in hydrometeorological data exists that is partly related to ENSO events. Given the nonstationary and nonlinear character of the ENSO-related changes in rainfall, we used the Hilbert-Huang transformation to detrend the time series of the river flow data from inter- and intra-annual fluctuations in rainfall. After applying adaptive data analysis based on empirical model decomposition techniques, it becomes apparent that the long-term trend in streamflow is different from the long-term trend in rainfall data. While the streamflow data show a long-term decrease in monthly flow, the rainfall data have a

Adding the human dimension to drought: an example from Chile

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Rangecroft, Sally; Van Loon, Anne; Maureira, Héctor; Rojas, Pablo; Alejandro Gutiérrez Valdés, Sergio; Verbist, Koen

2016-04-01

Drought and water scarcity are important hazards and can lead to severe socio-economic impacts in many regions of the world. Given the interlinked interactions and feedbacks of hydrological droughts and their impacts and management, we need tools to evaluate these complexities and effects on the availability of water resources. Here we use a real-world case study of the Huasco basin (Northern Chile) in which we quantify the influence of human activities on hydrological drought signals. In this arid region, Andean snowmelt provides water essential for users, with agriculture acting as the main water consumer (85% of total). An increasing water demand from different water sectors (agriculture, mining, and domestic water usage) has increased pressure on available water and its management. Consequently, the Santa Juana dam was built by 1995 to increase irrigation security for downstream users, and recent management and restrictions have been established with the objective to limit impacts of hydrological droughts across the basin. The feedbacks between water availability and water management are explored for this water stressed region in Chile. Hydro-meteorological (e.g. precipitation, temperature, streamflow, reservoir levels) variables have been analysed to assess trends and drought patterns. Data over the past three decades has indicated a decrease in surface water supply, with the basin entering a situation of water scarcity during the recent multiyear drought (2007 - to-date), partly caused by meteorological drought and partly by abstraction. During this period, water supply failed to meet the demands of water users, resulting in the implementation of water restrictions. As well as the necessary continuous hydro-meteorological data, here we used information on human water users and scenario modeling, allowing for the analysis and quantification of feedbacks. This work highlights the importance of local knowledge, especially in understanding water laws, rights

Streamflow Gaging Stations

Data.gov (United States)

Department of Homeland Security — This map layer shows selected streamflow gaging stations of the United States, Puerto Rico, and the U.S. Virgin Islands, in 2013. Gaging stations, or gages, measure...

From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

Science.gov (United States)

Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

2016-02-01

This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

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Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

Time Series MODIS and in Situ Data Analysis for Mongolia Drought

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Munkhzul Dorjsuren

2016-06-01

Full Text Available Drought is a period of abnormally dry weather with a serious shortage of water supply. Drought indices can be an advantageous indicator to assess drought for taking further response actions. However, drought indices based on ground meteorological measurements could not completely reveal the land use effects over a regional scale. On the other hand, the satellite-derived products provide consistent, spatial and temporal comparisons of global signatures for the regional-scale drought events. This research is to investigate the drought signatures over Mongolia by using satellite remote sensing imagery. The evapotranspiration (ET, potential evapotranspiration (PET and two-band Enhanced Vegetation Index (EVI2 were extracted from MODIS data. Based on the standardized ratio of ET to PET (ET/PET and EVI2, the Modified Drought Severity Index (MDSI anomaly during the growing season from May–August for the years 2000–2013 was acquired. Fourteen-year summer monthly data for air temperature, precipitation and soil moisture content of in situ measurements from sixteen meteorological stations for four various land use areas were analyzed. We also calculated the percentage deviation of climatological variables at the sixteen stations to compare to the MDSI anomaly. Both comparisons of satellite-derived and observed anomalies and variations were analyzed by using the existing common statistical methods. The results demonstrated that the air temperature anomaly (T anomaly and the precipitation anomaly (P anomaly were negatively (correlation coefficient r = −0.66 and positively (r = 0.81 correlated with the MDSI anomaly, respectively. The MDSI anomaly distributions revealed that the wettest area occupied 57% of the study area in 2003, while the driest (drought area occurred over 54% of the total area in 2007. The results also showed very similar variations between the MDSI and T anomalies. The highest (wettest MDSI anomaly indicated the lowest T anomaly

Monthly streamflow forecasting with auto-regressive integrated moving average

Science.gov (United States)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Characteristics and changes of streamflow on the Tibetan Plateau: A review

Directory of Open Access Journals (Sweden)

Lan Cuo

2014-11-01

New hydrological insights for the region: Streamflow follows the monthly patterns of precipitation and temperature in that all peak in May–September. Streamflow changes are affected by climate change and human activities depending on the basins. Streamflow is precipitation dominated in the northern, eastern and southeastern basins. In the central and western basin either melt water or groundwater, or both contributes significantly to streamflow. Human activities have altered streamflow in the lower reaches of the eastern, northern and western basins. Long-term trends in streamflow vary with basins. Outstanding research issues include: (1 What are the linkages between streamflow and climate systems? (2 What are the basin-wide hydrological processes? And (3 What are the cryospheric change impacts on hydrological processes and water balance?

Toward Seasonal Forecasting of Global Droughts: Evaluation over USA and Africa

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Wood, Eric; Yuan, Xing; Roundy, Joshua; Sheffield, Justin; Pan, Ming

2013-04-01

Extreme hydrologic events in the form of droughts are significant sources of social and economic damage. In the United States according to the National Climatic Data Center, the losses from drought exceed US210 billion during 1980-2011, and account for about 24% of all losses from major weather disasters. Internationally, especially for the developing world, drought has had devastating impacts on local populations through food insecurity and famine. Providing reliable drought forecasts with sufficient early warning will help the governments to move from the management of drought crises to the management of drought risk. After working on drought monitoring and forecasting over the USA for over 10 years, the Princeton land surface hydrology group is now developing a global drought monitoring and forecasting system using a dynamical seasonal climate-hydrologic LSM-model (CHM) approach. Currently there is an active debate on the merits of the CHM-based seasonal hydrologic forecasts as compared to Ensemble Streamflow Prediction (ESP). We use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2) and its previous version CFSv1, to investigate the value of seasonal climate model forecasts by conducting a set of 27-year seasonal hydrologic hindcasts over the USA. Through Bayesian downscaling, climate models have higher squared correlation (R2) and smaller error than ESP for monthly precipitation averaged over major river basins across the USA, and the forecasts conditional on ENSO show further improvements (out to four months) over river basins in the southern USA. All three approaches have plausible predictions of soil moisture drought frequency over central USA out to six months because of strong soil moisture memory, and seasonal climate models provide better results over central and eastern USA. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur

Droughts in historical times in Polish territory

Science.gov (United States)

Limanowka, Danuta; Cebulak, Elzbieta; Pyrc, Robert; Doktor, Radoslaw

2015-04-01

Climate change is one of the key environmental, social and economical issues, and it is also followed by political consequences. Impact of climate conditions on countries' economy is increasingly recognized, and a lot of attention is given, both in the global scale and by the individual national governments. In years 2008-2010, at the Poland -Institute of Meteorology and Water Management-National Research Institute was realized the KLIMAT Project on Impact of climate change on environment, economy and society (changes, effects and methods of reducing them, conclusions for science, engineering practice and economic planning) No. POIG01-03-01-14-011/08. The project was financed by the European Union and Polish state budget in frame of Innovative Economy Operational Programme. A very wide range of research was carried out in the different thematic areas. One of them was "Natural disasters and internal safety of the country (civil and economical)." The problem of drought in Poland was developed in terms of meteorology and hydrology. "Proxy" Data Descriptions very often inform about dry years and seasons, hot periods without precipitation. Analysis of historical material allowed to extract the years that have experienced prolonged periods of high temperatures and rainfall shortages. Weather phenomenon defined as drought belongs to extreme events. This information was very helpful in the process of indexing and thus to restore the course and intensity of climatic elements in the past. The analysis covered the period from year 1000 to modern times. Due to the limited information from the period of 1000-1500 the authors focused primarily on the period from 1500 to 2010. Analysis of the collected material has allowed the development of a highly precise temporal structure of the possible occurrence of dry periods to Polish territory.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

Science.gov (United States)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Rescaled range analysis of streamflow records in the São Francisco River Basin, Brazil

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Araujo, Marcelo Vitor Oliveira; Celeste, Alcigeimes B.

2018-01-01

Hydrological time series are sometimes found to have a distinctive behavior known as long-term persistence, in which subsequent values depend on each other even under very large time scales. This implies multiyear consecutive droughts or floods. Typical models used to generate synthetic hydrological scenarios, widely used in the planning and management of water resources, fail to preserve this kind of persistence in the generated data and therefore may have a major impact on projects whose design lives span for long periods of time. This study deals with the evaluation of long-term persistence in streamflow records by means of the rescaled range analysis proposed by British engineer Harold E. Hurst, who first observed the phenomenon in the mid-twentieth century. In this paper, Hurst's procedure is enhanced by a strategy based on statistical hypothesis testing. The case study comprises the six main hydroelectric power plants located in the São Francisco River Basin, part of the Brazilian National Grid. Historical time series of inflows to the major reservoirs of the system are investigated and 5/6 sites show significant persistence, with values for the so-called Hurst exponent near or greater than 0.7, i.e., around 40% above the value 0.5 that represents a white noise process, suggesting that decision makers should take long-term persistence into consideration when conducting water resources planning and management studies in the region.

Systemic and intensifying drought induces collapse and replacement of native fishes: a time-series approach

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Ruhi, A.; Olden, J. D.; Sabo, J. L.

2015-12-01

In the American Southwest, hydrologic drought has become a new normal as a result of increasing human appropriation of freshwater resources and increased aridity associated with global warming. Although drought has often been touted to threaten freshwater biodiversity, connecting drought to extinction risk of highly-imperiled faunas remains a challenge. Here we combine time-series methods from signal processing and econometrics to analyze a spatially comprehensive and long-term dataset to link discharge variation and community abundance of fish across the American Southwest. This novel time series framework identifies ongoing trends in daily discharge anomalies across the Southwest, quantifies the effect of the historical hydrologic drivers on fish community abundance, and allows us to simulate species trajectories and range-wide risk of decline (quasiextinction) under scenarios of future climate. Spectral anomalies are declining over the last 30 years in at least a quarter of the stream gaging stations across the American Southwest and these anomalies are robust predictors of historical abundance of native and non-native fishes. Quasiextinction probabilities are high (>50 %) for nearly ¾ of the native species across several large river basins in the same region; and the negative trend in annual anomalies increases quasiextinction risk for native but reduces this risk for non-native fishes. These findings suggest that ongoing drought is causing range-wide collapse and replacement of native fish faunas, and that this homogenization of western fish faunas will continue given the prevailing negative trend in discharge anomalies. Additionally, this combination of methods can be applied elsewhere as long as environmental and biological long-term time-series data are available. Collectively, these methods allow identifying the link between hydroclimatic forcing and ecological responses and thus may help anticipating the potential impacts of ongoing and future hydrologic

Land Use Change Increases Streamflow Across the Arc of Deforestation in Brazil

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Levy, M. C.; Lopes, A. V.; Cohn, A.; Larsen, L. G.; Thompson, S. E.

2018-04-01

Nearly half of recent decades' global forest loss occurred in the Amazon and Cerrado (tropical savanna) biomes of Brazil, known as the arc of deforestation. Despite prior analysis in individual river basins, a generalizable empirical understanding of the effect of deforestation on streamflow across this region is lacking. We frame land use change in Brazil as a natural experiment and draw on in situ and remote sensing evidence in 324 river basins covering more than 3 × 106 km2 to estimate streamflow changes caused by deforestation and agricultural development between 1950 and 2013. Deforestation increased dry season low flow by between 4 and 10 percentage points (relative to the forested condition), corresponding to a regional- and time-averaged rate of increase in specific streamflow of 1.29 mm/year2, equivalent to a 4.08 km3/year2 increase, assuming a stationary climate. In conjunction with rainfall and temperature variations, the net (observed) average increase in streamflow over the same period was 0.76 mm/year2, or 2.41 km3/year2. Thus, net increases in regional streamflow in the past half century are 58% of those that would have been experienced with deforestation given a stationary climate. This study uses a causal empirical analysis approach novel to the water sciences to verify the regional applicability of prior basin-scale studies, provides a proof of concept for the use of observational causal identification methods in the water sciences, and demonstrates that deforestation masks the streamflow-reducing effects of climate change in this region.

Modeling drought impact occurrence based on climatological drought indices for four European countries

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Stagge, James H.; Kohn, Irene; Tallaksen, Lena M.; Stahl, Kerstin

2014-05-01

The relationship between atmospheric conditions and the likelihood of a significant drought impact has, in the past, been difficult to quantify, particularly in Europe where political boundaries and language have made acquiring comprehensive drought impact information difficult. As such, the majority of studies linking meteorological drought with the occurrence or severity of drought impacts have previously focused on specific regions, very detailed impact types, or both. This study describes a new methodology to link the likelihood of drought impact occurrence with climatological drought indices across different European climatic regions and impact sectors using the newly developed European Drought Impact report Inventory (EDII), a collaborative database of drought impact information (www.geo.uio.no/edc/droughtdb/). The Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) are used as predictor variables to quantify meteorological drought severity over prior time periods (here 1, 2, 3, 6, 9, 12, and 24 months are used). The indices are derived using the gridded WATCH Forcing Datasets, covering the period 1958-2012. Analysis was performed using logistic regression to identify the climatological drought index and accumulation period, or linear combination of drought indices, that best predicts the likelihood of a documented drought impact, defined by monthly presence/absence. The analysis was carried out for a subset of four European countries (Germany, UK, Norway, Slovenia) and four of the best documented impact sectors: Public Water Supply, Agriculture and Livestock Farming, Energy and Industry, and Environmental Quality. Preliminary results show that drought impacts in these countries occur most frequently due to a combination of short-term (2-6 month) precipitation deficits and long-term (12-24 month) potential evapotranspiration anomaly, likely associated with increased temperatures. Agricultural drought impacts

Computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data

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Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Doug; Ziegler, Andrew C.

2010-01-01

Over the last decade, use of a method for computing suspended-sediment concentration and loads using turbidity sensors—primarily nephelometry, but also optical backscatter—has proliferated. Because an in- itu turbidity sensor is capa le of measuring turbidity instantaneously, a turbidity time series can be recorded and related directly to time-varying suspended-sediment concentrations. Depending on the suspended-sediment characteristics of the measurement site, this method can be more reliable and, in many cases, a more accurate means for computing suspended-sediment concentrations and loads than traditional U.S. Geological Survey computational methods. Guidelines and procedures for estimating time s ries of suspended-sediment concentration and loading as a function of turbidity and streamflow data have been published in a U.S. Geological Survey Techniques and Methods Report, Book 3, Chapter C4. This paper is a summary of these guidelines and discusses some of the concepts, s atistical procedures, and techniques used to maintain a multiyear suspended sediment time series.

Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

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Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen

2016-07-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction

Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan

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Kuo, Chun-Chao; Gan, Thian Yew; Yu, Pao-Shan

2010-06-01

SummaryA combined, climate-hydrologic system with three components to predict the streamflow of two river basins of Taiwan at one season (3-month) lead time for the NDJ and JFM seasons was developed. The first component consists of the wavelet-based, ANN-GA model (Artificial Neural Network calibrated by Genetic Algorithm) which predicts the seasonal rainfall by using selected sea surface temperature (SST) as predictors, given that SST are generally predictable by climate models up to 6-month lead time. For the second component, three disaggregation models, Valencia and Schaake (VS), Lane, and Canonical Random Cascade Model (CRCM), were tested to compare the accuracy of seasonal rainfall disaggregated by these three models to 3-day time scale rainfall data. The third component consists of the continuous rainfall-runoff model modified from HBV (called the MHBV) and calibrated by a global optimization algorithm against the observed rainfall and streamflow data of the Shihmen and Tsengwen river basins of Taiwan. The proposed system was tested, first by disaggregating the predicted seasonal rainfall of ANN-GA to rainfall of 3-day time step using the Lane model; then the disaggregated rainfall data was used to drive the calibrated MHBV to predict the streamflow for both river basins at 3-day time step up to a season's lead time. Overall, the streamflow predicted by this combined system for the NDJ season, which is better than that of the JFM season, will be useful for the seasonal planning and management of water resources of these two river basins of Taiwan.

Analysing the Effects of Forest Cover and Irrigation Farm Dams on Streamflows of Water-Scarce Catchments in South Australia through the SWAT Model

Directory of Open Access Journals (Sweden)

Hong Hanh Nguyen

2017-01-01

Full Text Available To assist water resource managers with future land use planning efforts, the eco-hydrological model Soil and Water Assessment Tool (SWAT was applied to three catchments in South Australia that experience extreme low flow conditions. Particular land uses and management issues of interest included forest covers, known to affect water yields, and farm dams, known to intercept and change the hydrological dynamics in a catchment. The study achieved a satisfactory daily calibration when irrigation farm dams were incorporated in the model. For the catchment dominated by extreme low flows, a better daily simulation across a range of qualitative and quantitative metrics was gained using the base-flow static threshold optimization technique. Scenario analysis on effects of forest cover indicated an increase of surface flow and a reduction of base-flow when native eucalyptus lands were replaced by pastures and vice versa. A decreasing trend was observed for the overall water yield of catchments with more forest plantation due to the higher evapotranspiration (ET rate and the decline in surface flow. With regards to effects of irrigation farm dams, assessment on a daily time step suggested that a significant volume of water is stored in these systems with the water loss rate highest in June and July. On an annual basis, the model indicated that approximately 13.1% to 22.0% of water has been captured by farm dams for irrigation. However, the scenario analysis revealed that the purposes of use of farm dams rather than their volumetric capacities in the catchment determined the magnitude of effects on streamflows. Water extracted from farm dams for irrigation of orchards and vineyards are more likely to diminish streamflows than other land uses. Outputs from this study suggest that the water use restrictions from farm dams during recent drought periods were an effective tool to minimize impacts on streamflows.

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

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Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

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Konapala, Goutam; Mishra, Ashok

2017-12-01

The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought

Streamflow monitoring and statistics for development of water rights claims for Wild and Scenic Rivers, Owyhee Canyonlands Wilderness, Idaho, 2012

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Wood, Molly S.; Fosness, Ryan L.

2013-01-01

The U.S. Geological Survey, in cooperation with the Bureau of Land Management (BLM), collected streamflow data in 2012 and estimated streamflow statistics for stream segments designated "Wild," "Scenic," or "Recreational" under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by BLM to develop and file a draft, federal reserved water right claim in autumn 2012 to protect federally designated "outstanding remarkable values" in the stream segments. BLM determined that the daily mean streamflow equaled or exceeded 20 and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull streamflow are important streamflow thresholds for maintaining outstanding remarkable values. Prior to this study, streamflow statistics estimated using available datasets and tools for the Owyhee Canyonlands Wilderness were inaccurate for use in the water rights claim. Streamflow measurements were made at varying intervals during February–September 2012 at 14 monitoring sites; 2 of the monitoring sites were equipped with telemetered streamgaging equipment. Synthetic streamflow records were created for 11 of the 14 monitoring sites using a partial‑record method or a drainage-area-ratio method. Streamflow records were obtained directly from an operating, long-term streamgage at one monitoring site, and from discontinued streamgages at two monitoring sites. For 10 sites analyzed using the partial-record method, discrete measurements were related to daily mean streamflow at a nearby, telemetered “index” streamgage. Resulting regression equations were used to estimate daily mean and annual peak streamflow at the monitoring sites during the full period of record for the index sites. A synthetic streamflow record for Sheep Creek was developed using a drainage-area-ratio method, because measured streamflows did not relate well to any index site to allow use of the partial

Future Drought Projections over the Iberian Peninsula using Drought Indices

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Garcia-Valdecasas Ojeda, M.; Yeste Donaire, P.; Góngora García, T. M.; Gámiz-Fortis, S. R.; Castro-Diez, Y.; Esteban-Parra, M. J.

2017-12-01

Currently, drought events are the cause of numerous annual economic losses. In a context of climate change, it is expected an increase in the severity and the frequency of drought occurrences, especially in areas such as the Mediterranean region. This study makes use of two drought indices in order to analyze the potential changes on future drought events and their effects at different time scales over a vulnerable region, the Iberian Peninsula. The indices selected were the Standardized Precipitation Evapotranspiration Index (SPEI), which takes into account the global warming through the temperature, and the Standardized Precipitation Index (SPI), based solely on precipitation data, at a spatial resolution of 0.088º ( 10 km). For their computation, current (1980-2014) and future (2021-2050 and 2071-2100) high resolution simulations were carried out using the Weather Research and Forecasting (WRF) model over a domain centered in the Iberian Peninsula, and nested in the 0.44 EUROCORDEX region. WRF simulations were driven by two different global bias-corrected climate models: the version 1 of NCAR's Community Earth System Model (CESM1) and the Max Planck Institute's Earth System Model (MPI-ESM-LR), and under two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Future projections were analyzed regarding to changes in mean, median and variance of drought indices with respect to the historical distribution, as well as changes in the frequency and duration of moderate and severe drought events. In general, results suggest an increase in frequency and severity of drought, especially for 2071-2100 period in the RCP 8.5 scenario. Results also shown an increase of drought phenomena more evident using the SPEI. Conclusions from this study could provide a valuable contribution to the understanding of how the increase of the temperature would affect the drought variability in the Mediterranean regions which is necessary for a suitable

Improving Federal Response to Drought.

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Wilhite, Donald A.; Rosenberg, Norman J.; Glantz, Michael H.

1986-03-01

Severe and widespread drought occurred over a large portion of the United States between 1974 and 1977. Impacts on agriculture and other industries, as well as local water supplies, were substantial. The federal government responded with forty assistance programs administered by sixteen federal agencies. Assistance was provided primarily in the form of loans and grants to people, businesses and governments experiencing hardship caused by drought. The total cost of the program is estimated at $7-8 billion.Federal response to the mid-1970s drought was largely untimely, ineffective and poorly coordinated. Four recommendations are offered that, if implemented, would improve future drought assessment and response efforts: 1) reliable and timely informational products and dissemination plans; 2) improved impact assessment techniques, especially in the agricultural sector, for use by government to identify periods of enhanced risk and to trigger assistance measures; 3) administratively centralized drought declaration procedures that are well publicized and consistently applied; and 4) standby assistance measures that encourage appropriate levels of risk management by producers and that are equitable, consistent and predictable. The development of a national drought plan that incorporates these four items is recommended. Atmospheric scientists have an important role to play in the collection and interpretation of near-real time weather data for use by government decision makers.

Macroinvertebrate community change associated with the severity of streamflow alteration

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Carlisle, Daren M.; Eng, Kenny; Nelson, S.M.

2014-01-01

Natural streamflows play a critical role in stream ecosystems, yet quantitative relations between streamflow alteration and stream health have been elusive. One reason for this difficulty is that neither streamflow alteration nor ecological responses are measured relative to their natural expectations. We assessed macroinvertebrate community condition in 25 mountain streams representing a large gradient of streamflow alteration, which we quantified as the departure of observed flows from natural expectations. Observed flows were obtained from US Geological Survey streamgaging stations and discharge records from dams and diversion structures. During low-flow conditions in September, samples of macroinvertebrate communities were collected at each site, in addition to measures of physical habitat, water chemistry and organic matter. In general, streamflows were artificially high during summer and artificially low throughout the rest of the year. Biological condition, as measured by richness of sensitive taxa (Ephemeroptera, Plecoptera and Trichoptera) and taxonomic completeness (O/E), was strongly and negatively related to the severity of depleted flows in winter. Analyses of macroinvertebrate traits suggest that taxa losses may have been caused by thermal modification associated with streamflow alteration. Our study yielded quantitative relations between the severity of streamflow alteration and the degree of biological impairment and suggests that water management that reduces streamflows during winter months is likely to have negative effects on downstream benthic communities in Utah mountain streams. 

Application of the geological streamflow and Muskingum Cunge ...

African Journals Online (AJOL)

... of the geological streamflow and Muskingum Cunge models in the Yala River Basin, Kenya. ... can be represented by the application of hydrologic and hydraulic models. ... verification and streamflow routing based on a split record analysis.

Watershed-scale modeling of streamflow change in incised montane meadows

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Essaid, Hedeff I.; Hill, Barry R.

2014-01-01

Land use practices have caused stream channel incision and water table decline in many montane meadows of the Western United States. Incision changes the magnitude and timing of streamflow in water supply source watersheds, a concern to resource managers and downstream water users. The hydrology of montane meadows under natural and incised conditions was investigated using watershed simulation for a range of hydrologic conditions. The results illustrate the interdependence between: watershed and meadow hydrology; bedrock and meadow aquifers; and surface and groundwater flow through the meadow for the modeled scenarios. During the wet season, stream incision resulted in less overland flow and interflow and more meadow recharge causing a net decrease in streamflow and increase in groundwater storage relative to natural meadow conditions. During the dry season, incision resulted in less meadow evapotranspiration and more groundwater discharge to the stream causing a net increase in streamflow and a decrease in groundwater storage relative to natural meadow conditions. In general, for a given meadow setting, the magnitude of change in summer streamflow and long-term change in watershed groundwater storage due to incision will depend on the combined effect of: reduced evapotranspiration in the eroded meadow; induced groundwater recharge; replenishment of dry season groundwater storage depletion in meadow and bedrock aquifers by precipitation during wet years; and groundwater storage depletion that is not replenished by precipitation during wet years.

Assessing Agricultural Drought in the Anthropocene: A Modified Palmer Drought Severity Index

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Mingzhi Yang

2017-09-01

Full Text Available In the current human-influenced era, drought is initiated by natural and human drivers, and human activities are as integral to drought as meteorological factors. In large irrigated agricultural regions with high levels of human intervention, where the natural farmland soil moisture has usually been changed significantly by high-frequency irrigation, the actual severity of agricultural drought is distorted in traditional drought indices. In this work, an agricultural drought index that considering irrigation processes based on the Palmer drought severity index (IrrPDSI was developed to interpret the real agricultural drought conditions in irrigated regions, with a case study in the Haihe River Basin in northeast China. The water balance model in the original PDSI was revised by an auto-irrigation threshold method combined with a local irrigation schedule. The auto-irrigation setting of the index was used by taking irrigation quotas during specific growth stages of specific crops (wheat–corn into consideration. A series of weekly comparative analyses are as follows: (1 The soil moisture analyses showed that soil moisture values calculated by the modified water balance model were close to the real values; (2 The statistical analyses indicated that most of the stations in the study area based on IrrPDSI had nearly normal distributed values; (3 The time series and spatial analyses showed that the results of the IrrPDSI-reported dry-wet evaluation were more consistent with documented real conditions. All the results revealed that IrrPDSI performed well when used to assess agricultural drought. This work has direct significance for agricultural drought management in large irrigated areas heavily disturbed by human activity.

The U.S./Canadian GEO Bilateral Drought Indices and Definitions Study: Implications for the Canadian Drought Monitor and a Global Drought Early Warning System

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Hadwen, T.; Heim, R. R.; Howard, A.

2011-12-01

Drought is a difficult phenomenon to define; the way in which it is monitored, measured, assessed and even the very definition of drought vary from location to location based on the regional climate and the potential impacts. Drought is not an absolute condition but an evolving state brought on by relatively dry weather, growing more severe over time. There are many factors that define a drought and many more that define its impacts. Many definitions and indices are based solely on meteorological characteristics. Although this approach has merit, it is often necessary to go further to define those meteorological conditions in a way that is relevant to the land and water use in a region. A Drought Indices and Definitions Study was initiated in 2010 as part of a GEO Bilateral effort to examine drought across the U.S. and Canada. The Study's deliverables will include a survey of the drought indices used to monitor drought, and a bibliography of research addressing the nature of drought, across the diverse climates of the continent. With an increasing pressure to utilize drought monitoring as a primary indicator of need for disaster assistance, the reliability of drought indices must be validated and utilized in appropriate in various regions. In 2009, following over five years of participation in the North American Drought Monitor (NA-DM), the National Agroclimate Information Service of Agriculture and Agri-Food Canada initiated a project to develop a Canadian Drought Monitor (Can-DM), based on primary principles used in the NA-DM and the US Drought Monitor (US-DM). The process of developing an operational monitoring tool and using drought indices in a vast and environmentally diverse country has been challenging. in Canada, many of the commonly used indices are not appropriate in certain regions or data densities do not allow for proper use. This paper will discuss the experiences that the Can-DM team has had dealing with these challenges, how these experiences

Evaluation of groundwater droughts in Austria

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Haas, Johannes Christoph; Birk, Steffen

2015-04-01

Droughts are abnormally dry periods that affect various aspects of human life on earth, ranging from negative impacts on agriculture or industry, to being the cause for conflict and loss of human life. The changing climate reinforces the importance of investigations into this phenomenon. Various methods to analyze and classify droughts have been developed. These include drought indices such as the Standard Precipitation Index SPI, the Palmer Drought Severity Index PDSI or the Crop Moisture Index CMI. These and other indices consider meteorological parameters and/or their effects on soil moisture. A depletion of soil moisture triggered by low precipitation and high evapotranspiration may also cause reduced groundwater recharge and thus decreasing groundwater levels and reduced groundwater flow to springs, streams, and wetlands. However, the existing indices were generally not designed to address such drought effects on groundwater. Thus, a Standardized Groundwater level Index has recently been proposed by Bloomfied and Marchant (2013). Yet, to our knowledge, this approach has only been applied to consolidated aquifers in the UK. This work analyzes time series of groundwater levels from various, mostly unconsolidated aquifers in Austria in order to characterize the effects of droughts on aquifers in different hydrogeologic and climatic settings as well as under different usage scenarios. In particular, comparisons are made between the water rich Alpine parts of Austria, and the dryer parts situated in the East. The time series of groundwater levels are compared to other data, such as meteorological time series and written weather records about generally accepted phenomena, such as the 2003 European drought and heat wave. Thus, valuable insight is gained into the propagation of meteorological droughts through the soil and the aquifer in different types of hydrogeologic and climatic settings, which provides a prerequisite for the assessment of the aquifers' drought

The SPEIbase: a new gridded product for the analysis of drought variability and drought impacts

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Begueria-Portugues, S.; Vicente-Serrano, S. M.; López-Moreno, J. I.; Angulo-Martínez, M.; El Kenawy, A.

2010-09-01

Recently a new drought indicator, the Standardised Precipitation-Evapotranspiration Index (SPEI), has been proposed to quantify the drought condition over a given area. The SPEI considers not only precipitation but also evapotranspiration (PET) data on its calculation, allowing for a more complete approach to explore the effects of climate change on drought conditions. The SPEI can be calculated at several time scales to adapt to the characteristic times of response to drought of target natural and economic systems, allowing determining their resistance to drought. Following the formulation of the SPEI a global dataset, the SPEIbase, has been made available to the scientific community. The dataset covers the period 1901-2006 with a monthly frequency, and offers global coverage at a 0.5 degrees resolution. The dataset consists on the monthly values of the SPEI at the time scales from 1 to 48 months. A description of the data and metadata, and links to download the files, are provided at http://sac.csic.es/spei. On this communication we will detail the methodology for computing the SPEI and the characteristics of the SPEIbase. A thorough discussion of the SPEI index, and some examples of use, will be provided in a companion comunication.

Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages

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Granato, Gregory E.; Ries, Kernell G.; Steeves, Peter A.

2017-10-16

Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.

Streamflow characteristics of the Colorado River Basin in Utah through September 1981

Science.gov (United States)

Christensen, R.C.; Johnson, E.B.; Plantz, G.G.

1987-01-01

 This report summarizes discharge data and other streamflow characteristics developed from gag ing-station records collected through September 1981 at 337 stations in the Colorado River Basin in Utah. Data also are included for 14 stations in adjacent areas of the bordering states of Arizona, Colorado, and Wyoming (fig. 1). The study leading to this report was done in cooperation with the U.S. Bureau of Land Management, which needs the streamflow data in order to evaluate impacts of mining on the hydrologic system. The report also will be beneficial to other Federal, State, and county agencies and to individuals concerned with water supply and water problems in the Colorado River Basin.The streamflow characteristics in the report could be useful in many water-related studies that involve the following:Definition of baseline-hydrologic conditions; studies of the effects of man's activities on streamflow; frequency analyses of low and high flows; regional analyses of streamflow characteristics; design of water-supply systems; water-power studies; forecasting of stream discharge; time-series analyses of streamflow; design of flood-control structures; stream-pollution studies; and water-chemistry transport studies.The basic data used to develop the summaries in this report are records of daily and peak discharge collected by the U.S. Geological Survey and other Federal agencies. Much of the work of the Geological Survey was done in cooperation with Federal, State, and county agencies. Discharge recordsincluded in the report generally were for stations with at least 1 complete water year of record and nearby stations that were on the same stream and had different streamflow characteristics. A water year is a 12-month period ending September 30, and it is designated by the calendar year in which it ends. For streams that have had significant changes in regulation by reservoirs or diversions, the records before and after those changes were used separately to provide

Streamflow impacts of biofuel policy-driven landscape change.

Directory of Open Access Journals (Sweden)

Sami Khanal

Full Text Available Likely changes in precipitation (P and potential evapotranspiration (PET resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979-2004 using the Weather Research Forecast (WRF model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

Science.gov (United States)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

Science.gov (United States)

Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

2018-01-01

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

Drivers of annual to decadal streamflow variability in the lower Colorado River Basin

Science.gov (United States)

Lambeth-Beagles, R. S.; Troch, P. A.

2010-12-01

The Colorado River is the main water supply to the southwest region. As demand reaches the limit of supply in the southwest it becomes increasingly important to understand the dynamics of streamflow in the Colorado River and in particular the tributaries to the lower Colorado River. Climate change may pose an additional threat to the already-scarce water supply in the southwest. Due to the narrowing margin for error, water managers are keen on extending their ability to predict streamflow volumes on a mid-range to decadal scale. Before a predictive streamflow model can be developed, an understanding of the physical drivers of annual to decadal streamflow variability in the lower Colorado River Basin is needed. This research addresses this need by applying multiple statistical methods to identify trends, patterns and relationships present in streamflow, precipitation and temperature over the past century in four contributing watersheds to the lower Colorado River. The four watersheds selected were the Paria, Little Colorado, Virgin/Muddy, and Bill Williams. Time series data over a common period from 1906-2007 for streamflow, precipitation and temperature were used for the initial analysis. Through statistical analysis the following questions were addressed: 1) are there observable trends and patterns in these variables during the past century and 2) if there are trends or patterns, how are they related to each other? The Mann-Kendall test was used to identify trends in the three variables. Assumptions regarding autocorrelation and persistence in the data were taken into consideration. Kendall’s tau-b test was used to establish association between any found trends in the data. Initial results suggest there are two primary processes occurring. First, statistical analysis reveals significant upward trends in temperatures and downward trends in streamflow. However, there appears to be no trend in precipitation data. These trends in streamflow and temperature speak to

Towards Improved Understanding of Drought and Drought Impacts from Long Term Earth Observation Records

Science.gov (United States)

Champagne, C.; Wang, S.; Liu, J.; Hadwen, T. A.

2017-12-01

Drought is a complex natural disaster, which often emerges slowly, but can occur at various time scales and have impacts that are not well understood. Long term observations of drought intensity and frequency are often quantified from precipitation and temperature based indices or modelled estimates of soil water storage. The maturity of satellite based observations has created the potential to enhance the understanding of drought and drought impacts, particularly in regions where traditional data sets are limited by remoteness or inaccessibility, and where drought processes are not well-quantified by models. Long term global satellite data records now provide observations of key hydrological variables, including evaporation modelled from thermal sensors, soil moisture from microwave sensors, ground water from gravity sensors and vegetation condition that can be modelled from optical sensors. This study examined trends in drought frequency, intensity and duration over diverse ecoregions in Canada, including agricultural, grassland, forested and wetland areas. Trends in drought were obtained from the Canadian Drought Monitor as well as meteorological based indices from weather stations, and evaluated against satellite derived information on evaporative stress (Anderson et al. 2011), soil moisture (Champagne et al. 2015), terrestrial water storage (Wang and Li 2016) and vegetation condition (Davidson et al. 2009). Data sets were evaluated to determine differences in how different sensors characterize the hydrology and impacts of drought events from 2003 to 2016. Preliminary results show how different hydrological observations can provide unique information that can tie causes of drought (water shortages resulting from precipitation, lack of moisture storage or evaporative stress) to impacts (vegetation condition) that hold the potential to improve the understanding and classification of drought events.

Streamflow data assimilation in SWAT model using Extended Kalman Filter

Science.gov (United States)

Sun, Leqiang; Nistor, Ioan; Seidou, Ousmane

2015-12-01

The Extended Kalman Filter (EKF) is coupled with the Soil and Water Assessment Tools (SWAT) model in the streamflow assimilation of the upstream Senegal River in West Africa. Given the large number of distributed variables in SWAT, only the average watershed scale variables are included in the state vector and the Hydrological Response Unit (HRU) scale variables are updated with the a posteriori/a priori ratio of their watershed scale counterparts. The Jacobian matrix is calculated numerically by perturbing the state variables. Both the soil moisture and CN2 are significantly updated in the wet season, yet they have opposite update patterns. A case study for a large flood forecast shows that for up to seven days, the streamflow forecast is moderately improved using the EKF-subsequent open loop scheme but significantly improved with a newly designed quasi-error update scheme. The former has better performances in the flood rising period while the latter has better performances in the recession period. For both schemes, the streamflow forecast is improved more significantly when the lead time is shorter.

Long-range forecasting of intermittent streamflow

OpenAIRE

F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

2011-01-01

Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine th...

Long-range forecasting of intermittent streamflow

OpenAIRE

F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

2011-01-01

Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a probabilistic statistical model to forecast streamflow 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probabil...

Ecohydrological and subsurface controls on drought-induced contraction and disconnection of stream networks

Science.gov (United States)

Godsey, S.; Kirchner, J. W.; Whiting, J. A.

2016-12-01

Temporary headwater streams - both intermittent and ephemeral waterways - supply water to approximately 1/3 of the US population, and 60% of streams used for drinking water are temporary. Stream ecologists increasingly recognize that a gradient of processes across the drying continuum affect ecosystems at dynamic terrestrial-aquatic interfaces. Understanding the hydrological controls across that gradient of drying may improve management of these sensitive systems. One possible control on surface flows includes transpiration losses from either the riparian zone or the entire watershed. We mapped several stream networks under extreme low flow conditions brought on by severe drought in central Idaho and California in 2015. Compared to previous low-flow stream length estimates, the active drainage network had generally decreased by a very small amount across these sites, perhaps because stored water buffered the precipitation decrease, or because flowing channel heads are fixed by focused groundwater flow emerging at springs. We also examined the apparent sources of water for both riparian and hillslope trees using isotopic techniques. During drought conditions, we hypothesized that riparian trees - but not those far from flowing streams - would be sustained by streamflow recharging riparian aquifers, and thus would transpire water that was isotopically similar to streamflow because little soil water would remain available below the wilting point and stream water would be sustain those trees. We found a more complex pattern, but in most places stream water and water transpired by trees were isotopically distinct regardless of flow intermittency or tree location. We also found that hillslope trees outside of the riparian zone appeared to be using different waters from those used by riparian trees. Finally, we explore subsurface controls on network extent, showing that bedrock characteristics can influence network stability and contraction patterns.

An effective streamflow process model for optimal reservoir operation using stochastic dual dynamic programming

OpenAIRE

Raso , L.; Malaterre , P.O.; Bader , J.C.

2017-01-01

International audience; This article presents an innovative streamflow process model for use in reservoir operational rule design in stochastic dual dynamic programming (SDDP). Model features, which can be applied independently, are (1) a multiplicative process model for the forward phase and its linearized version for the backward phase; and (2) a nonuniform time-step length that is inversely proportional to seasonal variability. The advantages are (1) guaranteeing positive streamflow values...

Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

Science.gov (United States)

Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.

2017-01-01

Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the Veg

Trends in annual, seasonal, and monthly streamflow characteristics at 227 streamgages in the Missouri River watershed, water years 1960-2011

Science.gov (United States)

Norton, Parker A.; Anderson, Mark T.; Stamm, John F.

2014-01-01

The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.

Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

Science.gov (United States)

Chanda, Kironmala; Maity, Rajib; Sharma, Ashish; Mehrotra, Rajeshwar

2014-10-01

This paper characterizes the long-term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability-resilience-vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five-yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area

Towards a method to characterize temporary groundwater dynamics during droughts

Science.gov (United States)

Heudorfer, Benedikt; Stahl, Kerstin

2016-04-01

In order to improve our understanding of the complex mechanisms involved in the development, propagation and termination of drought events, a major challenge is to grasp the role of groundwater systems. Research on how groundwater responds to meteorological drought events (i.e. short-term climate anomalies) is still limited. Part of the problem is that there is as yet no generic method to characterize the response of different groundwater systems to extreme climate anomalies. In order to explore possibilities for such a methodology, we evaluate two statistical approaches to characterize groundwater dynamics on short time scales by applying them on observed groundwater head data from different pre- and peri-mountainous groundwater systems in humid central Europe (Germany). The first method is based on the coefficient of variation in moving windows of various lengths, the second method is based on streamflow recession characteristics applied on groundwater data. With these methods, the gauges behavior during low head events and its response to precipitation was explored. Findings regarding the behavior of the gauges make it possible to distinguish between gauges with a dominance of cyclic patterns, and gauges with a dominance of patterns on seasonal or event scale (commonly referred to as slow/fast responding gauges, respectively). While some clues on what factors that might control these patterns are present, the specific controls are general unclear for the gauges in this study. However as the key conclusion stands the question if the variety of manifestations of groundwater dynamics, as they occur in real systems, is subsumable with one unique method. Further studies on the topic are in progress.

The implications of drought and water conservation on the reuse of municipal wastewater: Recognizing impacts and identifying mitigation possibilities.

Science.gov (United States)

Tran, Quynh K; Jassby, David; Schwabe, Kurt A

2017-11-01

As water agencies continue to investigate opportunities to increase resilience and local water supply reliability in the face of drought and rising water scarcity, water conservation strategies and the reuse of treated municipal wastewater are garnering significant attention and adoption. Yet a simple water balance thought experiment illustrates that drought, and the conservation strategies that are often enacted in response to it, both likely limit the role reuse may play in improving local water supply reliability. For instance, as a particular drought progresses and agencies enact water conservation measures to cope with drought, influent flows likely decrease while influent pollution concentrations increase, particularly salinity, which adversely affects wastewater treatment plant (WWTP) costs and effluent quality and flow. Consequently, downstream uses of this effluent, whether to maintain streamflow and quality, groundwater recharge, or irrigation may be impacted. This is unfortunate since reuse is often heralded as a drought-proof mechanism to increase resilience. The objectives of this paper are two-fold. First, we illustrate-using a case study from Southern California during its most recent drought- how drought and water conservation strategies combine to reduce influent flow and quality and, subsequently, effluent flow and quality. Second, we use a recently developed regional water reuse decision support model (RWRM) to highlight cost-effective strategies that can be implemented to mitigate the impacts of drought on effluent water quality. While the solutions we identify cannot increase the flow of influent or effluent coming into or out of a treatment plant, they can improve the value of the remaining effluent in a cost-effective manner that takes into account the characteristics of its demand, whether it be for landscaping, golf courses, agricultural irrigation, or surface water augmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Operationalising resilience to drought: Multi-layered safety for flooding applied to droughts

Science.gov (United States)

Rijke, Jeroen; Smith, Jennifer Vessels; Gersonius, Berry; van Herk, Sebastiaan; Pathirana, Assela; Ashley, Richard; Wong, Tony; Zevenbergen, Chris

2014-11-01

This paper sets out a way of thinking about how to prepare for and respond to droughts in a holistic way using a framework developed for managing floods. It shows how the multi-layered safety (MLS) approach for flood resilience can be utilised in the context of drought in a way that three layers of intervention can be distinguished for operationalising drought resilience: (1) protection against water shortage through augmentation and diversification of water supplies; (2) prevention of damage in case of water shortage through increased efficiency of water use and timely asset maintenance; (3) preparedness for future water shortages through mechanisms to reduce the use of water and adopt innovative water technologies. Application of MLS to the cities of Adelaide, Melbourne and Sydney shows that recent water reforms in these cities were primarily focused on protection measures that aim to reduce the hazard source or exposure to insufficient water supplies. Prevention and preparedness measures could be considered in defining interventions that aim to further increase the drought resilience of these cities. Although further research is needed, the application suggests that MLS can be applied to the context of drought risk management. The MLS framework can be used to classify the suite of plans deployed by a city to manage future drought risks and can be considered a planning tool to identify opportunities for increasing the level of redundancy and hence resilience of the drought risk management system.

Simulating the effects of ground-water withdrawals on streamflow in a precipitation-runoff model

Science.gov (United States)

Zarriello, Philip J.; Barlow, P.M.; Duda, P.B.

2004-01-01

Precipitation-runoff models are used to assess the effects of water use and management alternatives on streamflow. Often, ground-water withdrawals are a major water-use component that affect streamflow, but the ability of surface-water models to simulate ground-water withdrawals is limited. As part of a Hydrologic Simulation Program-FORTRAN (HSPF) precipitation-runoff model developed to analyze the effect of ground-water and surface-water withdrawals on streamflow in the Ipswich River in northeastern Massachusetts, an analytical technique (STRMDEPL) was developed for calculating the effects of pumped wells on streamflow. STRMDEPL is a FORTRAN program based on two analytical solutions that solve equations for ground-water flow to a well completed in a semi-infinite, homogeneous, and isotropic aquifer in direct hydraulic connection to a fully penetrating stream. One analytical method calculates unimpeded flow at the stream-aquifer boundary and the other method calculates the resistance to flow caused by semipervious streambed and streambank material. The principle of superposition is used with these analytical equations to calculate time-varying streamflow depletions due to daily pumping. The HSPF model can readily incorporate streamflow depletions caused by a well or surface-water withdrawal, or by multiple wells or surface-water withdrawals, or both, as a combined time-varying outflow demand from affected channel reaches. These demands are stored as a time series in the Watershed Data Management (WDM) file. This time-series data is read into the model as an external source used to specify flow from the first outflow gate in the reach where these withdrawals are located. Although the STRMDEPL program can be run independently of the HSPF model, an extension was developed to run this program within GenScn, a scenario generator and graphical user interface developed for use with the HSPF model. This extension requires that actual pumping rates for each well be stored

Making the Case for a Water Monitor: A Potential Complement to the U.S. Drought Monitor within a Water Management Context

Science.gov (United States)

Svoboda, M. D.; Fuchs, B.; Poulsen, C.; Nothwehr, J.; Swigart, J.

2017-12-01

Launched in 1999, the weekly U.S. Drought Monitor (USDM) is now approaching its twentieth year of existence. Over that time, it has built up an expert validation community that has grown into a network of nearly 450 persons. From the very beginning, questions from the user community have been centered on how we can do a better job of addressing and depicting short- vs. long-term conditions on a single map such as the U.S. Drought Monitor. Early efforts to fill the water supply/demand/forecast void have simply utilized existing hydrological websites and products from a variety of sources across a variety of spatial and temporal scales. The question being asked repeatedly has been "Why not develop two separate maps?" Can such an approach strengthen our capacity to assess both the supply and demand side of the equation when it comes to balancing drought and water supply? This presentation will describe in more detail the evolution of the USDM and how the need for a complementary sister product such as a Water Monitor has emerged. We will explore how such a tool could better capture and collectively assess key hydroclimatic parameters (e.g., in situ, modeled and remotely sensed products), better integrate streamflow forecasts, and reflect surface and groundwater resources and snow water equivalent. In essence, the goal is to develop a more usable decision support tool that has the potential to better facilitate water management and markets in the United States. Ultimately, there are vast differences between the USDM and Water Monitor products that we must address in order to better reflect how drought affects both managed and unmanaged systems.

Comprehensive Characterization of Droughts to Assess the Effectiveness of a Basin-Wide Integrated Water Management in the Yakima River Basin

Science.gov (United States)

Demissie, Y.; Mortuza, M. R.; Li, H. Y.

2017-12-01

Better characterization and understanding of droughts and their potential links to climate and hydrologic factors are essential for water resources planning and management in drought-sensitive but agriculturally productive regions like the Yakima River Basin (YKB) in Washington State. The basin is semi-arid and heavily relies on a fully appropriated irrigation water for fruit and crop productions that worth more than 3 billion annually. The basin experienced three major droughts since 2000 with estimated 670 million losses in farm revenue. In response to these and expected worsening drought conditions in the future, there is an ongoing multi-agency effort to adopt a basin-wide integrated water management to ensure water security during severe droughts. In this study, the effectiveness of the proposed water management plan to reduce the frequency and severity of droughts was assessed using a new drought index developed based on the seasonal variations of precipitation, temperature, snow accumulation, streamflow, and reservoir storages. In order to uncover the underlying causes of the various types of droughts observed during the 1961-2016, explanatory data analysis using deep learning was conducted for the local climate and hydrologic data including total water supply available, as well as global climatic phenomenon (El Niño/Southern Oscillation, Pacific Decadal Oscillation and North Atlantic Oscillation). The preliminary results showed that besides shortage in annual precipitation, various combinations of climate and hydrologic factors are responsible for the different drought conditions in the basin. Particularly, the winter snowpack, which provides about 2/3 of the surface water in the basin along with the carryover storage from the reservoirs play an important role during both single- and multiple-year drought events. Besides providing the much-needed insights about characteristics of droughts and their contributing factors, the outcome of the study is expected

Streamflow profile classification using functional data analysis: A case study on the Kelantan River Basin

Science.gov (United States)

Jamaludin, Suhaila

2017-05-01

Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape.

Bacterial mediated amelioration of drought stress in drought tolerant ...

African Journals Online (AJOL)

Bacterial mediated amelioration of drought stress in drought tolerant and susceptible cultivars of rice ( Oryza sativa L.) ... and IR-64 (drought sensitive) cultivars of rice (Oryza sativa L.) under different level of drought stress. ... from 32 Countries:.

Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

Science.gov (United States)

Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

2016-12-01

The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

A review of methods for monitoring streamflow for sustainable water resource management

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Dobriyal, Pariva; Badola, Ruchi; Tuboi, Chongpi; Hussain, Syed Ainul

2017-10-01

Monitoring of streamflow may help to determine the optimum levels of its use for sustainable water management in the face of climate change. We reviewed available methods for monitoring streamflow on the basis of six criteria viz. their applicability across different terrains and size of the streams, operational ease, time effectiveness, accuracy, environmental impact that they may cause and cost involve in it. On the basis of the strengths and weaknesses of each of the methods reviewed, we conclude that the timed volume method is apt for hilly terrain having smaller streams due to its operational ease and accuracy of results. Although comparatively expensive, the weir and flume methods are suitable for long term studies of small hill streams, since once the structure is put in place, it yields accurate results. In flat terrain, the float method is best suited for smaller streams for its operational ease and cost effectiveness, whereas, for larger streams, the particle image velocimetry may be used for its accuracy. Our review suggests that the selection of a method for monitoring streamflow may be based on volume of the stream, accuracy of the method, accessibility of the terrain and financial and physical resources available.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Science.gov (United States)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Effects of drought on avian community structure

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Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Brian D. Wardlow; Volker C. Radeloff

2010-01-01

Droughts are expected to become more frequent under global climate change. Avifauna depend on precipitation for hydration, cover, and food. While there are indications that avian communities respond negatively to drought, little is known about the response of birds with differing functional and behavioural traits, what time periods and indicators of drought are most...

Drought, Agriculture, and Labor: Understanding Drought Impacts and Vulnerability in California

Science.gov (United States)

Greene, C.

2015-12-01

Hazardous drought impacts are a product of not only the physical intensity of drought, but also the economic, social, and environmental characteristics of the region exposed to drought. Drought risk management requires understanding the complex links between the physical and human dimensions of drought. Yet, there is a research gap in identifying and explaining the socio-economic complexities of drought in the context of the first world, especially for economic and socially marginal groups who rely on seasonal and temporary jobs. This research uses the current drought in California as a case study to identify the socioeconomic impacts of drought on farmworker communities in California's San Joaquin Valley, with a specific focus on the relationship between drought and agricultural labor. Through both a narrative analysis of drought coverage in newspaper media, drought policy documents, and interviews with farmworkers, farmers, community based organizations, and government officials in the San Joaquin Valley, this research aims to highlight the different understandings and experiences of the human impacts of drought and drought vulnerability in order to better inform drought risk planning and policy.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

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Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature

Developing Drought Outlook Forums in Support of a Regional Drought Early Warning Information System

Science.gov (United States)

Mcnutt, C. A.; Pulwarty, R. S.; Darby, L. S.; Verdin, J. P.; Webb, R. S.

2011-12-01

The National Integrated Drought Information System (NIDIS) Act of 2006 (P.L. 109-430) charged NIDIS with developing the leadership and partnerships necessary to implement an integrated national drought monitoring and forecasting system that creates a drought "early warning system". The drought early warning information system should be capable of providing accurate, timely and integrated information on drought conditions at the relevant spatial scale to facilitate proactive decisions aimed at minimizing the economic, social and ecosystem losses associated with drought. As part of this effort, NIDIS has held Regional Drought Outlook Forums in several regions of the U.S. The purpose of the Forums is to inform practices that reduce vulnerability to drought through an interactive and collaborative process that includes the users of the information. The Forums have focused on providing detailed assessments of present conditions and impacts, comparisons with past drought events, and seasonal predictions including discussion of the state and expected evolution of the El Niño Southern Oscillation phenomena. Regional Climate Outlook Forums (RCOFs) that include close interaction between information providers and users are not a new concept, however. RCOFs started in Africa in the 1990s in response to the 1997-98 El Niño and have since expanded to South America, Asia, the Pacific islands, and the Caribbean. As a result of feedback from the RCOFs a large body of research has gone into improving seasonal forecasts and the capacity of the users to apply the information in a way that improves their decision-making. Over time, it has become clear that more is involved than just improving the interaction between the climate forecasters and decision-makers. NIDIS is using the RCOF approach as one component in a larger effort to develop Regional Drought Early Warning Information Systems (RDEWS) around the U.S. Using what has been learned over the past decade in the RCOF process

Streamflow of 2016—Water year summary

Science.gov (United States)

Jian, Xiaodong; Wolock, David M.; Lins, Harry F.; Brady, Steven J.

2017-09-26

The maps and graphs in this summary describe national streamflow conditions for water year 2016 (October 1, 2015, to September 30, 2016) in the context of streamflow ranks relative to the 87-year period of 1930–2016, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Network. The period of 1930–2016 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. Runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another.In all the graphics, a rank of 1 indicates the highest flow of all years analyzed and 87 indicates the lowest flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively). Some of the data used to produce the maps and graphs are provisional and subject to change.

Influence of mathematical and physical background of drought indices on their complementarity and drought recognition ability

Science.gov (United States)

Frank, Anna; Armenski, Tanja; Gocic, Milan; Popov, Srdjan; Popovic, Ljiljana; Trajkovic, Slavisa

2017-09-01

The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation - Evapotranspiration Index (SPEI) - 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process.

Global drought outlook by means of seasonal forecasts

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Ziese, Markus; Fröhlich, Kristina; Rustemeier, Elke; Becker, Andreas

2017-04-01

Droughts are naturally occurring phenomena which are caused by a shortage of available water due to lower than normal precipitation and/or above normal evaporation. Depending on the length of the droughts, several sectors are affected starting with agriculture, then river and ground water levels and finally socio-economic losses at the long end of the spectrum of drought persistence. Droughts are extreme events that affect much larger areas and last much longer than floods, but are less geared towards media than floods being more short-scale in persistence and impacts. Finally the slow onset of droughts make the detection and early warning of their beginning difficult and time is lost for preparatory measures. Drought indices are developed to detect and classify droughts based on (meteorological) observations and possible additional information tailored to specific user needs, e.g. in agriculture, hydrology and other sectors. Not all drought indices can be utilized for global applications as not all input parameters are available at this scale. Therefore the Global Precipitation Climatology Centre (GPCC) developed a drought index as combination of the Standardized Drought Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), the GPCC-DI. The GPCC-DI is applied to drought monitoring and retrospective analyses on a global scale. As the Deutscher Wetterdienst (DWD) operates a seasonal forecast system in cooperation with Max-Planck-Institute for Meteorology Hamburg and University of Hamburg, these data are also used for an outlook of drought conditions by means of the GPCC-DI. The reliability of seasonal precipitation forecasts is limited, so the drought outlook is available only for forecast months two to four. Based on the GPCC-DI, DWD provides a retrospective analysis, near-real-time monitoring and outlook of drought conditions on a global scale and regular basis.

Winter cyclone frequency and following freshet streamflow formation on the rivers in Belarus

Science.gov (United States)

Partasenok, Irina S.; Groisman, Pavel Ya; Chekan, Grigoriy S.; Melnik, Viktor I.

2014-09-01

We studied long-term fluctuations of streamflow and occurrence of extreme phenomena on the rivers of Belarus during the post-World War II period. It was found that formation of annual runoff within the nation has no constant tendencies and varies from year to year. At the same time, analysis of intra-annual distribution of streamflow reveals significant changes since the 1970s, first of all, increase of winter and decrease of spring streamflow. As a result, the frequency of extreme floods has decreased. These changes in water regime are associated with climatic anomalies (increase of the surface air temperatures) caused by large-scale alterations in atmospheric circulation, specifically in trajectories of cyclones. During the last two decades, the frequency of Atlantic and southern cyclones has changed and caused decreasing of cold season storms and extreme phenomena on the rivers.

A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

Science.gov (United States)

Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

' (SHARP) to implement, assess and demonstrate real-time over-the-loop ensemble flow forecasts in a range of US watersheds. The system relies on fully ensemble techniques, including: an 100-member ensemble of meteorological model forcings and an ensemble particle filter data assimilation for initializing watershed states; analog/regression-based downscaling of ensemble weather forecasts from GEFS; and statistical post-processing of ensemble forecast outputs, all of which run in real-time within a workflow managed by ECWMF's ecFlow libraries over large US regional domains. We describe SHARP and present early hindcast and verification results for short to seasonal range streamflow forecasts in a number of US case study watersheds.

Evaluation of bias-correction methods for ensemble streamflow volume forecasts

Directory of Open Access Journals (Sweden)

T. Hashino

2007-01-01

Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA on Streamflow.

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Ryan R Bart

Full Text Available Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm, with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow

Science.gov (United States)

Tague, Christina L.; Moritz, Max A.

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. PMID:27575592

Financial vulnerability of the electricity sector to drought, and the impacts of changes in generation mix

Science.gov (United States)

Kern, J.

2015-12-01

Electric power utilities are increasingly cognizant of the risks water scarcity and rising temperatures pose for generators that use water as a "fuel" (i.e., hydroelectric dams) and generators that use water for cooling (i.e., coal, natural gas and nuclear). At the same time, utilities are under increasing market and policy pressure to retire coal-fired generation, the primary source of carbon emissions in the electric power sector. Due to falling costs of renewables and low natural gas prices, retiring coal fired generation is mostly being replaced with combined cycle natural gas, wind and solar. An immediate benefit of this shift has been a reduction in water withdrawals per megawatt-hour and reduced thermal impacts in surface water systems. In the process of retiring older coal-fired power plants, many of which use water intensive open-loop cooling systems, utilities are making their systems less vulnerable to water scarcity and higher water temperatures. However, it is not clear whether financial risks from water scarcity will decrease as result of this change. In particular, the choice to replace coal with natural gas combined cycle plants leaves utilities financially exposed to natural gas prices, especially during droughts when natural gas generation is used to replace lost hydropower production. Utility-scale solar, while more expensive than natural gas combined cycle generation, gives utilities an opportunity to simultaneously reduce their exposure to water scarcity and fuel price risk. In this study, we assess how switching from coal to natural gas and solar changes a utility's financial exposure to drought. We model impacts on retail prices and a utility's rate of return under current conditions and non-stationarity in natural gas prices and temperature and streamflows to determine whether increased exposure to natural gas prices offsets corresponding gains in water use efficiency. We also evaluate whether utility scale solar is an effective hedge

Drought occurence

Science.gov (United States)

John W. Coulston

2007-01-01

Why Is Drought Important? Drought is an important forest disturbance that occurs regularly in the Western United States and irregularly in the Eastern United States (Dale and others 2001). Moderate drought stress tends to slow plant growth while severedrought stress can also reduce photosynthesis (Kareiva and others 1993). Drought can also interact with...

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

Science.gov (United States)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Prediction of Missing Streamflow Data using Principle of Information Entropy

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Santosa, B.

2014-01-01

Full Text Available Incomplete (missing of streamflow data often occurs. This can be caused by a not continous data recording or poor storage. In this study, missing consecutive streamflow data are predicted using the principle of information entropy. Predictions are performed ​​using the complete monthly streamflow information from the nearby river. Data on average monthly streamflow used as a simulation sample are taken from observation stations Katulampa, Batubeulah, and Genteng, which are the Ciliwung Cisadane river areas upstream. The simulated prediction of missing streamflow data in 2002 and 2003 at Katulampa Station are based on information from Genteng Station, and Batubeulah Station. The mean absolute error (MAE average obtained was 0,20 and 0,21 in 2002 and the MAE average in 2003 was 0,12 and 0,16. Based on the value of the error and pattern of filled gaps, this method has the potential to be developed further.

Analysis of streamflow response to land use and land cover changes using satellite data and hydrological modelling: case study of Dinder and Rahad tributaries of the Blue Nile (Ethiopia-Sudan)

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Hassaballah, Khalid; Mohamed, Yasir; Uhlenbrook, Stefan; Biro, Khalid

2017-10-01

Understanding the land use and land cover changes (LULCCs) and their implication on surface hydrology of the Dinder and Rahad basins (D&R, approximately 77 504 km2) is vital for the management and utilization of water resources in the basins. Although there are many studies on LULCC in the Blue Nile Basin, specific studies on LULCC in the D&R are still missing. Hence, its impact on streamflow is unknown. The objective of this paper is to understand the LULCC in the Dinder and Rahad and its implications on streamflow response using satellite data and hydrological modelling. The hydrological model has been derived by different sets of land use and land cover maps from 1972, 1986, 1998 and 2011. Catchment topography, land cover and soil maps are derived from satellite images and serve to estimate model parameters. Results of LULCC detection between 1972 and 2011 indicate a significant decrease in woodland and an increase in cropland. Woodland decreased from 42 to 14 % and from 35 to 14 % for Dinder and Rahad, respectively. Cropland increased from 14 to 47 % and from 18 to 68 % in Dinder and Rahad, respectively. The model results indicate that streamflow is affected by LULCC in both the Dinder and the Rahad rivers. The effect of LULCC on streamflow is significant during 1986 and 2011. This could be attributed to the severe drought during the mid-1980s and the recent large expansion in cropland.

Rehab: Drought and famine in Ethiopia

Energy Technology Data Exchange (ETDEWEB)

Hussein, A.M.

1976-01-01

A Special Report on the two Ethiopian drought-famine crises is reviewed. The Wollo drought occurred at the same time as the West African. Although drought also hit Sudan, and thus spread from the Atlantic to the Red Sea, Ethiopia's drought seems to have been unique, for its normal rainfall pattern is different from that of the Sahel; there are two rainy seasons, linked to a wind system more complex than that in West Africa. The limited data on this is summarized in S. Betheke's chapter of Rehap. This is an important study which helps impact an understanding of the revolution provoked by the Imperial regime's handling of the northern famine, and also allows useful comparisons of the Ethiopian and West African drought crisis.

Diverse multi-decadal changes in streamflow within a rapidly urbanizing region

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Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.

2018-01-01

The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing

Interaction between stream temperature, streamflow, and groundwater exchanges in alpine streams

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Constantz, James E.

1998-01-01

Four alpine streams were monitored to continuously collect stream temperature and streamflow for periods ranging from a week to a year. In a small stream in the Colorado Rockies, diurnal variations in both stream temperature and streamflow were significantly greater in losing reaches than in gaining reaches, with minimum streamflow losses occurring early in the day and maximum losses occurring early in the evening. Using measured stream temperature changes, diurnal streambed infiltration rates were predicted to increase as much as 35% during the day (based on a heat and water transport groundwater model), while the measured increase in streamflow loss was 40%. For two large streams in the Sierra Nevada Mountains, annual stream temperature variations ranged from 0° to 25°C. In summer months, diurnal stream temperature variations were 30–40% of annual stream temperature variations, owing to reduced streamflows and increased atmospheric heating. Previous reports document that one Sierra stream site generally gains groundwater during low flows, while the second Sierra stream site may lose water during low flows. For August the diurnal streamflow variation was 11% at the gaining stream site and 30% at the losing stream site. On the basis of measured diurnal stream temperature variations, streambed infiltration rates were predicted to vary diurnally as much as 20% at the losing stream site. Analysis of results suggests that evapotranspiration losses determined diurnal streamflow variations in the gaining reaches, while in the losing reaches, evapotranspiration losses were compounded by diurnal variations in streambed infiltration. Diurnal variations in stream temperature were reduced in the gaining reaches as a result of discharging groundwater of relatively constant temperature. For the Sierra sites, comparison of results with those from a small tributary demonstrated that stream temperature patterns were useful in delineating discharges of bank storage following

Risk across disciplines: An interdisciplinary examination of water and drought risk in South-Central Oklahoma

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Lazrus, H.; Paimazumder, D.; Towler, E.; McPherson, R. A.

2013-12-01

Drought is a challenge faced by communities across the United States, exacerbated by growing demands on water resources and climate variability and change. The Arbuckle-Simpson Aquifer (ASA) in south-central Oklahoma, situated in the heart of the Chickasaw Nation, is the state's only sole-source groundwater basin and sustains the Blue River, the state's only free-flowing river. The recent comprehensive hydrological studies of the aquifer indicate the need for sustainable management of the amount of water extracted. However, the question of how to deal with that management in the face of increasing drought vulnerability, diverse demands, and climate variability and change remains. Water management carries a further imperative to be inclusive of tribal and non-tribal interests. To examine this question, we are conducting an investigation of drought risk from multiple disciplines. Anthropological data comes from stakeholder interviews that were designed to investigate conflict over water management by understanding how people perceive risk differently based on different opinions about the structure of the resource, varying levels of trust in authorities, and unequal access to resources. . The Cultural Theory of Risk is used to explain how people view risks as part of their worldviews and why people who hold different worldviews disagree about risks associated with water availability. Meteorological analyses of longitudinal data indicate periods of drought that are noted in stakeholder interviews. Analysis of stream gauge data investigates the influence of climate variability on local hydrologic impacts, such as changing groundwater levels and streamflows, that are relevant to planning and management decisions in the ASA. Quantitative assessment of future drought risk and associated uncertainty and their effect on type and scale of future economic and social impacts are achieved by combining elements of statistical and dynamical downscaling to improve predictions of

A Global Drought Observatory for Emergency Response

Science.gov (United States)

Vogt, Jürgen; de Jager, Alfred; Carrão, Hugo; Magni, Diego; Mazzeschi, Marco; Barbosa, Paulo

2016-04-01

Droughts are occurring on all continents and across all climates. While in developed countries they cause significant economic and environmental damages, in less developed countries they may cause major humanitarian catastrophes. The magnitude of the problem and the expected increase in drought frequency, extent and severity in many, often highly vulnerable regions of the world demand a change from the current reactive, crisis-management approach towards a more pro-active, risk management approach. Such approach needs adequate and timely information from global to local scales as well as adequate drought management plans. Drought information systems are important for continuous monitoring and forecasting of the situation in order to provide timely information on developing drought events and their potential impacts. Against this background, the Joint Research Centre (JRC) is developing a Global Drought Observatory (GDO) for the European Commission's humanitarian services, providing up-to-date information on droughts world-wide and their potential impacts. Drought monitoring is achieved by a combination of meteorological and biophysical indicators, while the societal vulnerability to droughts is assessed through the targeted analysis of a series of social, economic and infrastructural indicators. The combination of the information on the occurrence and severity of a drought, on the assets at risk and on the societal vulnerability in the drought affected areas results in a likelihood of impact, which is expressed by a Likelihood of Drought Impact (LDI) indicator. The location, extent and magnitude of the LDI is then further analyzed against the number of people and land use/land cover types affected in order to provide the decision bodies with information on the potential humanitarian and economic bearings in the affected countries or regions. All information is presented through web-mapping interfaces based on OGC standards and customized reports can be drawn by the

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow.

Science.gov (United States)

Bart, Ryan R; Tague, Christina L; Moritz, Max A

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.

The effects of changing land cover on streamflow simulation in Puerto Rico

Science.gov (United States)

Van Beusekom, Ashley; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Statistical of the drought in Colombia

International Nuclear Information System (INIS)

Hurtado Moreno, Gonzalo

1994-01-01

The drought is evaluated by means of a standardized index of precipitation, at the same time simple and direct. It has not been guided toward a specific type of drought, but rather it has been evaluated as a phenomenon caused exclusively by the rain deficiency

Alteration of streamflow magnitudes and potential ecological consequences: A multiregional assessment

Science.gov (United States)

Carlisle, Daren M.; Wolock, David M.; Meador, Michael R.

2011-01-01

Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream-flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine-grained substrates and slow-moving currents, as well as the ability to temporarily leave the aquatic environment.

Potentials of molecular based breeding to enhance drought ...

African Journals Online (AJOL)

The ability of plant to sustain itself in limited water conditions is crucial in the world of agriculture. To breed for drought tolerance in wheat, it is essential to clearly understand drought tolerant mechanisms. Conventional breeding is time consuming and labor intensive being inefficient with low heritability traits like drought ...

Partitioning uncertainty in streamflow projections under nonstationary model conditions

Science.gov (United States)

Chawla, Ila; Mujumdar, P. P.

2018-02-01

Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them

EFFECT OF DROUGHT ON STRESS IN PLANTS

Directory of Open Access Journals (Sweden)

Jelena Marković

2015-07-01

Full Text Available Drought occurs due to lack of water in the soil, as well as due to disturbances in the circulation of the atmosphere. The duration of the drought may be different, and droughts not only the lack of rainfall, but also erratic distribution of rainfall throughout the year. The intensity of droughts amplified high temperatures, low relative humidity and dry, hot winds. The drought in many areas of common occurrence that repeats without a discernible regularity. Although it can be found in almost all parts of the world, its characteristics vary from region to region. Defining drought is therefore difficult and depends on regional differences and needs, but also from the perspective from which to observe this phenomenon. In the broadest sense, the drought is due to the lack of precipitation over an extended period of time, leading to water shortages for some activities, group activities or an entire sector of the environment. Drought can not be viewed solely as a physical phenomenon. The occurrence of drought, because of the weather, a lot of influences and reflects on the plants and agricultural production.

Climate Engine - Monitoring Drought with Google Earth Engine

Science.gov (United States)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

The potential of SMAP soil moisture data for analyzing droughts

Science.gov (United States)

Rajasekaran, E.; Das, N. N.; Entekhabi, D.; Yueh, S. H.

2017-12-01

Identification of the onset and the end of droughts are important for socioeconomic planning. Different datasets and tools are either available or being generated for drought analysis to recognize the status of drought. The aim of this study is to understand the potential of the SMAP soil moisture (SM) data for identification of onset, persistence and withdrawal of droughts over the Contiguous United States. We are using the SMAP-passive level 3 soil moisture observations and the United States Drought Monitor (http://droughtmonitor.unl.edu) data for understanding the relation between change in SM and drought severity. The daily observed SM data are temporally averaged to match the weekly drought monitor data and subsequently the weekly, monthly, 3 monthly and 6 monthly change in SM and drought severity were estimated. The analyses suggested that the change in SM and drought severity are correlated especially over the mid-west and west coast of USA at monthly and longer time scales. The spatial pattern of the SM change maps clearly indicated the regions that are moving between different levels of drought severity. Further, the time series of effective saturation [Se =(θ-θr)/(θs-θr)] indicated the temporal dynamics of drought conditions over California which is recovering from a long-term drought. Additional analyses are being carried out to develop statistics between drought severity and soil moisture level.

An intercomparison of approaches for improving operational seasonal streamflow forecasts

Science.gov (United States)

Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.

2017-07-01

For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches - statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) - and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction - HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically

California's Drought - Stress test for the future

Science.gov (United States)

Lund, J. R.

2014-12-01

The current California drought is in its third dry years, with this year being the third driest years in a 106-year record. This drought occurs at a time when urban, agricultural, and environmental water demands have never been greater. This drought has revealed the importance of more quantitative evaluation and methods for water assessment and management. All areas of water and environmental management are likely to become increasingly stressed, and have essentially drought-like conditions, in the future, as California's urban, agricultural, and environmental demands continue to expand and as the climate changes. In the historical past, droughts have pre-viewed stresses developing in the future and helped focus policy-makers, the public, and stakeholders on preparing for these developing future conditions. Multi-decade water management strategies are often galvinized by drought. Irrigation was galvanized by California droughts in the 1800s, reservoir systems by the 1928-32 drought, urban water conservation by the 1976-77 drought, and water markets by the 1988-92 drought. With each drought, demands for tighter accounting, rights, and management have increased. This talk reviews the prospects and challenges for increased development and use of water data and systems analysis in the service of human and environmental water demands in California's highly decentralized water management system, and the prospects if these challenges are not more successfully addressed.

Rainwater harvesting for drought disaster alleviation

International Nuclear Information System (INIS)

Widodo, B.; Prinzand, D.; Malik, A.H.

2005-01-01

Too little water and too much water can be as devastating as well. Drought usually does not show up instantly like flood, but it creeps slowly. Drought that is less popular than flood has impact more serious than flood. It is difficult to be identified when it comes and when it goes away. However, it is suddenly understood when water becomes scare, or no more water is available in wells, rivers and reservoirs. Managing flood and drought has to be at an integrated basis. Rainwater harvesting (RWH) combined with water conservation methods can be developed to alleviate drought disaster as well as flood disaster in the same time. RWH and water conservation must be an integral part of integrated water resources management. Preventing drought could be automatically reducing the extent of flood that means preventing people and the environment from the disasters. (author)

Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

Science.gov (United States)

Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

2018-03-01

Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

Drought, Climate Change and the Canadian Prairies

Science.gov (United States)

Stewart, R. E.

2010-03-01

The occurrence of drought is a ubiquitous feature of the global water cycle. Such an extreme does not necessarily lead to an overall change in the magnitude of the global water cycle but it of course affects the regional cycling of water. Droughts are recurring aspects of weather and climate extremes as are floods and tornadoes, but they differ substantially since they have long durations and lack easily identified onsets and terminations. Drought is a relatively common feature of the North American and Canadian climate system and all regions of the continent are affected from time-to-time. However, it tends to be most common and severe over the central regions of the continent. The Canadian Prairies are therefore prone to drought. Droughts in the Canadian Prairies are distinctive in North America. The large scale atmospheric circulations are influenced by blocking from intense orography to the west and long distances from all warm ocean-derived atmospheric water sources; growing season precipitation is generated by a highly complex combination of frontal and convective systems; seasonality is severe and characterized by a relatively long snow-covered and short growing seasons; local surface runoff is primarily produced by snowmelt water; there is substantial water storage potential in the poorly drained, post-glacial topography; and aquifers are overlain by impermeable glacial till, but there are also important permeable aquifers. One example of Prairie drought is the recent one that began in 1999 with cessation of its atmospheric component in 2004/2005 and many of its hydrological components in 2005. This event produced the worst drought for at least a hundred years in parts of the Canadian Prairies. Even in the dust bowl of the 1930s, no single year over the central Prairies were drier than in 2001. The drought affected agriculture, recreation, tourism, health, hydro-electricity, and forestry in the Prairies. Gross Domestic Product fell some 5.8 billion and

Risk identification of agricultural drought for sustainable Agroecosystems

Science.gov (United States)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-09-01

Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than

Arbuscular mycorrhizal symbiosis induces strigolactone biosynthesis under drought and improves drought tolerance in lettuce and tomato.

Science.gov (United States)

Ruiz-Lozano, Juan Manuel; Aroca, Ricardo; Zamarreño, Ángel María; Molina, Sonia; Andreo-Jiménez, Beatriz; Porcel, Rosa; García-Mina, José María; Ruyter-Spira, Carolien; López-Ráez, Juan Antonio

2016-02-01

Arbuscular mycorrhizal (AM) symbiosis alleviates drought stress in plants. However, the intimate mechanisms involved, as well as its effect on the production of signalling molecules associated with the host plant-AM fungus interaction remains largely unknown. In the present work, the effects of drought on lettuce and tomato plant performance and hormone levels were investigated in non-AM and AM plants. Three different water regimes were applied, and their effects were analysed over time. AM plants showed an improved growth rate and efficiency of photosystem II than non-AM plants under drought from very early stages of plant colonization. The levels of the phytohormone abscisic acid, as well as the expression of the corresponding marker genes, were influenced by drought stress in non-AM and AM plants. The levels of strigolactones and the expression of corresponding marker genes were affected by both AM symbiosis and drought. The results suggest that AM symbiosis alleviates drought stress by altering the hormonal profiles and affecting plant physiology in the host plant. In addition, a correlation between AM root colonization, strigolactone levels and drought severity is shown, suggesting that under these unfavourable conditions, plants might increase strigolactone production in order to promote symbiosis establishment to cope with the stress. © 2015 John Wiley & Sons Ltd.

Variance analysis of forecasted streamflow maxima in a wet temperate climate

Science.gov (United States)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

How soil moisture mediates the influence of transpiration on streamflow at hourly to interannual scales in a forested catchment

Science.gov (United States)

G.W. Moore; J.A. Jones; B.J. Bond

2011-01-01

The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to...

How do extreme streamflow due to hurricane IRMA compare during 1938-2017 in South Eastern US?

Science.gov (United States)

Anandhi, A.

2017-12-01

The question related to Irma, Harvey, Maria, and other hurricanes is: are hurricane more frequent and intense than they have been in the past. Recent hurricanes were unusually strong hitting the US Coastline or territories as a category 4 or 5, dropping unusually large amounts of precipitation on the affected areas creating extreme high-flow events in rivers and streams in affected areas. The objective of the study is to determine how extreme are streamflows from recent hurricanes (e.g. IRMA) when compared to streamflow's during 1938-2017 time-period. Additionally, in this study, the extreme precipitations are also compared during IRMA. Extreme high flows are selected from Indicators of Hydrologic Alteration (IHA). They are distributions, timing, duration, frequency, magnitude, pulses, and days of extreme events in rivers of the southeastern United States and Gulf of Mexico Hydrologic Region—03. Streamflow data from 30 stations in the region with at least 79 years of record (1938-2017) are used. Historical precipitation changes is obtained from meta-analysis of published literature. Our preliminary results indicate the extremeness of streamflow from recent hurricanes vary with the IHA indicator selected. Some potential implications of these extreme events on the region's ecosystem are also discussed using causal chains and loops.

Return to normal streamflows and water levels: summary of hydrologic conditions in Georgia, 2013

Science.gov (United States)

Knaak, Andrew E.; Caslow, Kerry; Peck, Michael F.

2015-01-01

The U.S. Geological Survey (USGS) South Atlantic Water Science Center (SAWSC) Georgia office, in cooperation with local, State, and other Federal agencies, maintains a long-term hydrologic monitoring network of more than 340 real-time continuous-record streamflow-gaging stations (streamgages), including 10 real-time lake-level monitoring stations, 67 real-time surface-water-quality monitors, and several water-quality sampling programs. Additionally, the SAWSC Georgia office operates more than 180 groundwater monitoring wells, 39 of which are real-time. The wide-ranging coverage of streamflow, reservoir, and groundwater monitoring sites allows for a comprehensive view of hydrologic conditions across the State. One of the many benefits of this monitoring network is that the analyses of the data provide a spatially distributed overview of the hydrologic conditions of creeks, rivers, reservoirs, and aquifers in Georgia.

Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information

Science.gov (United States)

Kumar, J.; Devineni, N.

2007-12-01

Information on season ahead stream flow forecasts is very beneficial for the operation and management of water supply systems. Daily streamflow conditions at any particular reservoir primarily depend on atmospheric and land surface conditions including the soil moisture and snow pack. On the other hand recent studies suggest that developing long lead streamflow forecasts (3 months ahead) typically depends on exogenous climatic conditions particularly Sea Surface Temperature conditions (SST) in the tropical oceans. Examples of some oceanic variables are El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Identification of such conditions that influence the moisture transport into a given basin poses many challenges given the nonlinear dependency between the predictors (SST) and predictand (stream flows). In this study, we apply both linear and nonlinear dependency measures to identify the predictors that influence the winter flows into the Neuse basin. The predictor identification approach here adopted uses simple correlation coefficients to spearman rank correlation measures for detecting nonlinear dependency. All these dependency measures are employed with a lag 3 time series of the high flow season (January - February - March) using 75 years (1928-2002) of stream flows recorded in to the Falls Lake, Neuse River Basin. Developing streamflow forecasts contingent on these exogenous predictors will play an important role towards improved water supply planning and management. Recently, the soft computing techniques, such as artificial neural networks (ANNs) have provided an alternative method to solve complex problems efficiently. ANNs are data driven models which trains on the examples given to it. The ANNs functions as universal approximators and are non linear in nature. This paper presents a study aiming towards using climatic predictors for 3 month lead time streamflow forecast. ANN models representing the physical process of the system are

Assessment of Meteorological Drought Indices in Korea Using RCP 8.5 Scenario

Directory of Open Access Journals (Sweden)

Dongwoo Jang

2018-03-01

Full Text Available Diverse drought indices have been developed and used across the globe to assess and monitor droughts. Among them, the Standardized Precipitation Index (SPI and Reconnaissance Drought Index (RDI are drought indices that have been recently developed and are being used in the world’s leading countries. This study took place in Korea’s major observatories for drought prediction until 2100, using the Representative Concentration Pathway (RCP 8.5 scenario. On the basis of the drought index measured by SPI, future climates were forecast to be humid, as the index would rise over time. In contrast, the RDI, which takes evapotranspiration into account, anticipated dry climates, with the drought index gradually falling over time. From the analysis of the drought index through the RCP 8.5 scenario, extreme drought intensity will be more likely to occur due to rising temperatures. To obtain the diversity of drought prediction, the evapotranspiration was deemed necessary for calculating meteorological droughts.

Decadal Drought and Wetness Reconstructed for Subtropical North America in the Mexican Drought Atlas

Science.gov (United States)

Burnette, D. J.; Stahle, D. W.; Cook, E. R.; Villanueva Diaz, J.; Griffin, D.; Cook, B.

2014-12-01

A new drought atlas has been developed for subtropical North America, including the entire Republic of Mexico. This Mexican Drought Atlas (MXDA) is based on 251 tree-ring chronologies, including 82 from Mexico and another 169 from the southern U.S. and western Guatemala. Point-by-point principal components regression was used to reconstruct the self-calibrating Palmer Drought Severity Index (PDSI) for June-August. Calibration and verification statistics were improved over what was previously possible with the North American Drought Atlas, which was based on fewer chronologies only in Mexico. The MXDA will be served on the web with analytical tools for composite, correlation, and congruence analyses. The new PDSI reconstructions provide a more detailed estimation of decadal moisture regimes over the past 2000 years, but are most robust after 1400 AD, when several chronologies are available across Mexico. Droughts previously identified in a subset of chronologies are confirmed and their spatial impact quantified in the new reconstructions. This includes the intense drought of the mid-15th Century described in Aztec legend, the 16th Century megadrought, and "El Año del Hambre", one of the worst famines in Mexican history. We also use the best replicated portion of the MXDA in the 18th and 19th Centuries to reconstruct moisture anomalies during key time periods of Mexican turmoil (e.g., the Mexican War of Independence).

Application of ANN and fuzzy logic algorithms for streamflow ...

Indian Academy of Sciences (India)

The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...

Origins of streamflow in a crystalline basement catchment in a sub-humid Sudanian zone: The Donga basin (Benin, West Africa): Inter-annual variability of water budget

Science.gov (United States)

Séguis, L.; Kamagaté, B.; Favreau, G.; Descloitres, M.; Seidel, J.-L.; Galle, S.; Peugeot, C.; Gosset, M.; Le Barbé, L.; Malinur, F.; Van Exter, S.; Arjounin, M.; Boubkraoui, S.; Wubda, M.

2011-05-01

SummaryDuring the last quarter of the 20th century, West Africa underwent a particularly intense and generalized drought. During this period, the biggest drops in streamflow were observed in the Sudanian zone rather than in the Sahelian zone, but the reasons are still poorly understood. In 2000, a meso-scale hydrological observatory was set up in the sub-humid Sudanian zone of the Upper Ouémé Valley (Benin). Three embedded catchments of 12-586 km 2 located on a crystalline bedrock were intensively instrumented to document the different terms of the water budget and to identify the main streamflow generating processes and base-flow mechanisms at different scales. Geophysical, hydrological and geochemical data were collected throughout the catchments from 2002 to 2006. Crossing these data helped define their hydrological functioning. The region has seasonal streamflow, and the permanent groundwater in the weathered mantle does not drain to rivers, instead, seasonal perched groundwaters are the major contributor to annual streamflow. The perched groundwaters are mainly located in seasonally waterlogged sandy layers in the headwater bottom-lands called bas-fonds in French-speaking West Africa of 1st order streams. During the period 2003-2006, regolith groundwater recharge ranged between 10% and 15% of the annual rainfall depth. Depletion of permanent groundwater during the dry season is probably explained by local evapotranspiration which was seen not to be limited to gallery forests. During the 4-year study period, a reduction of 20% in annual rainfall led to a 50% reduction in streamflow. This reduction was observed in the two components of the flow: direct runoff and drainage of perched groundwater. Thanks to the comprehensive dataset obtained, the results obtained for the Donga experimental catchment are now being extrapolated to the whole upper Ouémé valley, which can be considered as representative of sub-humid Sudanian rivers flowing on a crystalline

Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

Science.gov (United States)

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

The complex influence of ENSO on droughts in Ecuador

KAUST Repository

Vicente-Serrano, S. M.

2016-03-26

In this study, we analyzed the influence of El Niño–Southern Oscillation (ENSO) on the spatio-temporal variability of droughts in Ecuador for a 48-year period (1965–2012). Droughts were quantified from 22 high-quality and homogenized time series of precipitation and air temperature by means of the Standardized Precipitation Evapotranspiration Index. In addition, the propagation of two different ENSO indices (El Niño 3.4 and El Niño 1 + 2 indices) and other atmospheric circulation processes (e.g., vertical velocity) on different time-scales of drought severity were investigated. The results showed a very complex influence of ENSO on drought behavior across Ecuador, with two regional patterns in the evolution of droughts: (1) the Andean chain with no changes in drought severity, and (2) the Western plains with less severe and frequent droughts. We also detected that drought variability in the Andes mountains is explained by the El Niño 3.4 index [sea surface temperature (SST) anomalies in the central Pacific], whereas the Western plains are much more driven by El Niño 1 + 2 index (SST anomalies in the eastern Pacific). Moreover, it was also observed that El Niño and La Niña phases enhance droughts in the Andes and Western plains regions, respectively. The results of this work could be crucial for predicting and monitoring drought variability and intensity in Ecuador. © 2016 Springer-Verlag Berlin Heidelberg

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

Science.gov (United States)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate

Skills of General Circulation and Earth System Models in reproducing streamflow to the ocean: the case of Congo river

Science.gov (United States)

Santini, M.; Caporaso, L.

2017-12-01

Although the importance of water resources in the context of climate change, it is still difficult to correctly simulate the freshwater cycle over the land via General Circulation and Earth System Models (GCMs and ESMs). Existing efforts from the Climate Model Intercomparison Project 5 (CMIP5) were mainly devoted to the validation of atmospheric variables like temperature and precipitation, with low attention to discharge.Here we investigate the present-day performances of GCMs and ESMs participating to CMIP5 in simulating the discharge of the river Congo to the sea thanks to: i) the long-term availability of discharge data for the Kinshasa hydrological station representative of more than 95% of the water flowing in the whole catchment; and ii) the River's still low influence by human intervention, which enables comparison with the (mostly) natural streamflow simulated within CMIP5.Our findings suggest how most of models appear overestimating the streamflow in terms of seasonal cycle, especially in the late winter and spring, while overestimation and variability across models are lower in late summer. Weighted ensemble means are also calculated, based on simulations' performances given by several metrics, showing some improvements of results.Although simulated inter-monthly and inter-annual percent anomalies do not appear significantly different from those in observed data, when translated into well consolidated indicators of drought attributes (frequency, magnitude, timing, duration), usually adopted for more immediate communication to stakeholders and decision makers, such anomalies can be misleading.These inconsistencies produce incorrect assessments towards water management planning and infrastructures (e.g. dams or irrigated areas), especially if models are used instead of measurements, as in case of ungauged basins or for basins with insufficient data, as well as when relying on models for future estimates without a preliminary quantification of model biases.

Candidate genes for drought tolerance and improved productivity in ...

Indian Academy of Sciences (India)

Madhu

tropics. Improving drought tolerance and productivity is one of the most difficult tasks for cereal breeders. The diffi- culty arises from the diverse strategies adopted by plants themselves to combat drought stress depending on the timing,. Candidate genes for drought tolerance and improved productivity in rice (Oryza sativa L.).

Relative contributions of transient and steady state infiltration during ephemeral streamflow

Science.gov (United States)

Blasch, Kyle W.; Ferré, Ty P.A.; Hoffmann, John P.; Fleming, John B.

2006-01-01

Simulations of infiltration during three ephemeral streamflow events in a coarse‐grained alluvial channel overlying a less permeable basin‐fill layer were conducted to determine the relative contribution of transient infiltration at the onset of streamflow to cumulative infiltration for the event. Water content, temperature, and piezometric measurements from 2.5‐m vertical profiles within the alluvial sediments were used to constrain a variably saturated water flow and heat transport model. Simulated and measured transient infiltration rates at the onset of streamflow were about two to three orders of magnitude greater than steady state infiltration rates. The duration of simulated transient infiltration ranged from 1.8 to 20 hours, compared with steady state flow periods of 231 to 307 hours. Cumulative infiltration during the transient period represented 10 to 26% of the total cumulative infiltration, with an average contribution of approximately 18%. Cumulative infiltration error for the simulated streamflow events ranged from 9 to 25%. Cumulative infiltration error for typical streamflow events of about 8 hours in duration in is about 90%. This analysis indicates that when estimating total cumulative infiltration in coarse‐grained ephemeral stream channels, consideration of the transient infiltration at the onset of streamflow will improve predictions of the total volume of infiltration that may become groundwater recharge.

Heavy and frequent thinning promotes drought adaptation in Pinus sylvestris forests.

Science.gov (United States)

Sohn, Julia A; Hartig, Florian; Kohler, Martin; Huss, Jürgen; Bauhus, Jürgen

2016-10-01

Droughts and their negative effects on forest ecosystems are projected to increase under climate change for many regions. It has been suggested that intensive thinning could reduce drought impacts on established forests in the short-term. Most previous studies on the effect of thinning on drought impacts, however, have been confined to single forest sites. It is therefore still unclear how general and persisting the benefits of thinning are. This study assesses the potential of thinning to increase drought tolerance of the wide spread Scots pine (Pinus sylvestris) in Central Europe. We hypothesized (1) that increasing thinning intensity benefits the maintenance of radial growth of crop trees during drought (resistance) and its recovery following drought, (2) that those benefits to growth decrease with time elapsed since the last thinning and with stand age, and (3) that they may depend on drought severity as well as water limitations in pre- and post-drought periods. To test these hypotheses, we assessed the effects of thinning regime, stand age, and drought severity on radial growth of 129 Scots pine trees during and after drought events in four long-term thinning experiments in Germany. We found that thinning improved the recovery of radial growth following drought and to a lesser extent the growth resistance during a drought event. Growth recovery following drought was highest after the first thinning intervention and in recently and heavily thinned stands. With time since the last thinning, however, this effect decreased and could even become negative when compared to unthinned stands. Further, thinning helped to avoid an age-related decline in growth resistance (and recovery) following drought. The recovery following drought, but not the resistance during drought, was related to water limitations in the drought period. This is the first study that analyzed drought-related radial growth in trees of one species across several stands of different age. The

Controls on streamflow intermittence in the Colorado Front Range

Science.gov (United States)

Kampf, S. K.; Puntenney, K.; Martin, C.; Weber, R.; Gerlich, J.; Hammond, J. C.; Lefsky, M. A.

2017-12-01

Intermittent streams comprise more than 60% of the channel length in semiarid northern Colorado, yet little is known about their flow magnitude and timing. We used field surveys, stream sensors, and remote sensing to quantify spatial and temporal patterns of streamflow intermittence in the Cache la Poudre basin in 2016-2017. To evaluate potential controls on streamflow intermittence, we delineated the drainage area to each monitored point and quantified the catchment's mean precipitation, temperature, snow persistence, slope, aspect, vegetation type, soil type, and bedrock geology. During the period of study, most streams below 2500 m elevation and drainage areas >1 km2 had perennial flow, whereas nearly all streams with drainage areas <1 km2 had intermittent flow. For the high elevation intermittent streams, stream locations often differed substantially from the locations mapped in standard GIS data products. Initial analyses have identified no clearly quantifiable controls on flow duration of high elevation streams, but field observations indicate subsurface flow paths are important contributors to surface streams.

Drought Characterisation Using Ground and Remote Sensing Data

Science.gov (United States)

Hore, Sudipta Kumar; Werner, Micha; Maskey, Shreedhar

2016-04-01

The North-West of Bangladesh is frequently affected by drought, which may have profound impacts to different water related sectors. The characterisation and identification of drought is, however, challenging. Despite several standard drought indices being available it is important that indicators proposed in support of an effective drought management are related to the impacts drought may have. In this study we present the characterisation of drought in the districts of Rajshahi and Rangpur in North-Western Bangladesh. Drought indicators were developed using available temperature, precipitation, river discharge and groundwater level data, as well as from remotely sensed NDVI data. We compare these indicators to records of drought impacts to agriculture, fisheries and migration collected from relevant organisations, as well as through interviews with key stakeholders, key informants, and community leaders. The analysis shows that droughts occur frequently, with nine occurrences in the last 42 years, as found using common meteorological drought indicators. NDVI data corroborated these events, despite being only available from 2001. The agricultural sector was adversely impacted in all events, with impacts correlated to drought severity. Impacts to the fisheries sector were, however, reported only three times, though impacts to fisheries are less well recorded. Interestingly, the good relationship between meteorological drought indicators and agricultural impacts weakens in the last decade. This appears to be due to the intensification of irrigation using groundwater, with the declining groundwater levels found in Rajshahi district suggesting overexploitation of the resource, and the increasing importance of groundwater drought indicators. The study reveals the drought indicators that are important to the agriculture and fisheries sectors, and also tentative threshold values at which drought start to impact these sectors. Such sector relevant drought indicators, as

Analytical flow duration curves for summer streamflow in Switzerland

Science.gov (United States)

Santos, Ana Clara; Portela, Maria Manuela; Rinaldo, Andrea; Schaefli, Bettina

2018-04-01

This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of discharge-generating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research.

Blended Drought Index: Integrated Drought Hazard Assessment in the Cuvelai-Basin

Directory of Open Access Journals (Sweden)

Robert Luetkemeier

2017-07-01

Full Text Available Drought is one of the major threats to societies in Sub-Saharan Africa, as the majority of the population highly depends on rain-fed subsistence agriculture and traditional water supply systems. Hot-spot areas of potential drought impact need to be identified to reduce risk and adapt a growing population to a changing environment. This paper presents the Blended Drought Index (BDI, an integrated tool for estimating the impact of drought as a climate-induced hazard in the semi-arid Cuvelai-Basin of Angola and Namibia. It incorporates meteorological and agricultural drought characteristics that impair the population’s ability to ensure food and water security. The BDI uses a copula function to combine common standardized drought indicators that describe precipitation, evapotranspiration, soil moisture and vegetation conditions. Satellite remote sensing products were processed to analyze drought frequency, severity and duration. As the primary result, an integrated drought hazard map was built to spatially depict drought hot-spots. Temporally, the BDI correlates well with millet/sorghum yield (r = 0.51 and local water consumption (r = −0.45 and outperforms conventional indicators. In the light of a drought’s multifaceted impact on society, the BDI is a simple and transferable tool to identify areas highly threatened by drought in an integrated manner.

Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

Science.gov (United States)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

Directory of Open Access Journals (Sweden)

S. L. Sun

2012-07-01

Full Text Available To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m³ s⁻¹ yr⁻¹ and 1.29 m³ s⁻¹ yr⁻¹ at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m³ s⁻¹ yr⁻¹, Gaosha (1.12 m³ s⁻¹ yr⁻¹, and Xiashan (1.34 m³ s⁻¹ yr⁻¹, while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m³ s⁻¹ yr⁻¹. In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds.

For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3 under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1 for the period of 2061–2100. When the future changes in the soil water storage

Precipitation Reconstructions and Periods of Drought in the Upper Green River Basin, Wyoming, USA

Science.gov (United States)

Follum, M.; Barnett, A.; Bellamy, J.; Gray, S.; Tootle, G.

2008-12-01

Due to recent drought and stress on water supplies in the Colorado River Compact States, more emphasis has been placed on the study of water resources in the Upper Green River Basin (UGRB) of Wyoming, Utah, and Colorado. The research described here focuses on the creation of long-duration precipitation records for the UGRB using tree-ring chronologies. When combined with existing proxy streamflow reconstructions and drought frequency analysis, these records offer a detailed look at hydrologic variability in the UGRB. Approximately thirty-three existing tree ring chronologies were analyzed for the UGRB area. Several new tree ring chronologies were also developed to enhance the accuracy and the geographical diversity of the resulting tree-ring reconstructions. In total, three new Douglas-fir (Pseudotsuga menziesii) and four new limber pine (Pinus flexilis) sites were added to the available tree-ring chronologies in this area. Tree-ring based reconstructions of annual (previous July through current June) precipitation were then created for each of the seventeen sub-watersheds in the UGRB. Reconstructed precipitation records extend back to at least 1654 AD, with reconstructions for some sub-basins beginning pre-1500. Variance explained (i.e. adjusted R2) ranged from 0.41 to 0.74, and the reconstructions performed well in a variety of verification tests. Additional analyses focused on stochastic estimation of drought frequency and return period, and detailed comparisons between reconstructed records and instrumental observations. Overall, this work points to the prevalence of severe, widespread drought in the UGRB. These analyses also highlight the relative wetness and lack of sustained dry periods during the instrumental period (1895-Present). Such long- term assessments are, in turn, vital tools as the Compact States contemplate the "Law of the River" in the face of climate change and ever-growing water demands.

The effect of severe drought and management after drought on the ...

African Journals Online (AJOL)

The False Thornveld of the Eastern Cape experienced a particularly intense drought during the 1982/1983 growing season. Extensive grass mortality took place during the drought. After the drought, recovery was particularly sensitive to the post-drought management treatment applied. Veld that was grazed immediately ...

A watershed modeling approach to streamflow reconstruction from tree-ring records

International Nuclear Information System (INIS)

Saito, Laurel; Biondi, Franco; Salas, Jose D; Panorska, Anna K; Kozubowski, Tomasz J

2008-01-01

Insight into long-term changes of streamflow is critical for addressing implications of global warming for sustainable water management. To date, dendrohydrologists have employed sophisticated regression techniques to extend runoff records, but this empirical approach cannot directly test the influence of watershed factors that alter streamflow independently of climate. We designed a mechanistic watershed model to calculate streamflows at annual timescales using as few inputs as possible. The model was calibrated for upper reaches of the Walker River, which straddles the boundary between the Sierra Nevada of California and the Great Basin of Nevada. Even though the model incorporated simplified relationships between precipitation and other components of the hydrologic cycle, it predicted water year streamflows with correlations of 0.87 when appropriate precipitation values were used

Comprehensive Analysis of Drought Persistence, Hazard, and Recovery across the CONUS

Science.gov (United States)

Zarekarizi, M.; Ahmadi, B.; Moradkhani, H.

2017-12-01

Drought is a creeping intertwined natural hazard affecting society more than any other natural disaster and causing enormous damages on economy and ecosystems. Better understanding of potential drought hazard can help water managers and stakeholders devising mitigation plans to minimize the adverse effects of droughts. In this study, soil moisture, simulated by the Variable Infiltration Capacity (VIC) land surface model, is used to analyze the probability of agricultural drought with different severities across the CONUS. Due to the persistence of soil moisture, a drought episode at a particular time is affected by its earlier status; therefore, this study has utilized a Copula function to model the selected hydrologic variable over the time. The probability of drought intensity for each unit is presented spatially. If the unit remains in the drought condition at the same or lower intensity, drought persists and if it improves above a pre-defined threshold, the unit recovers. Results show that the west of US is more vulnerable to drought persistence in summer and spring while the Midwest and Northeast of US are experiencing drought persistence in fall and winter. In addition, the analysis reveals that as the intensity of drought in a given season decreases the following season has higher chance of recovery.

Agricultural Productivity Forecasts for Improved Drought Monitoring

Science.gov (United States)

Limaye, Ashutosh; McNider, Richard; Moss, Donald; Alhamdan, Mohammad

2010-01-01

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop

Development of a Precipitation-Runoff Model to Simulate Unregulated Streamflow in the Salmon Creek Basin, Okanogan County, Washington

Science.gov (United States)

van Heeswijk, Marijke

2006-01-01

Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of

IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia

Energy Technology Data Exchange (ETDEWEB)

Sahu, Netrananda; Yamashiki, Yosuke; Takara, Kaoru [Kyoto University, Disaster Prevention Research Institute, Innovative Disaster Prevention Technology and Policy Research Laboratory, Gokasho, Uji City, Kyoto (Japan); Behera, Swadhin K. [JAMSTEC, Research Institute for Global Change, Yokohama, Kanagawa (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan); Yamagata, Toshio [University of Tokyo, School of Science, Bunkyo-ku, Tokyo (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan)

2012-10-15

Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Nina conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Nino Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Nino events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Nino for September-November season only. (orig.)