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Karst spring water dynamic characteristics and its response to atmospheric precipitation are of great significance for water resources utilization under the background of climate change. This paper selects Longzici spring area, North China, as the study area. Based on a long series of spring water flow and precipitation data, the dynamic characteristics of spring flow were analyzed and the numerical simulation of the groundwater flow model was established. The results show that the groundwater kept the sustained decline over the past decades which is in a negative equilibrium state, with a storage variable of − 2.26 million m3/year. The sensitivity of spring flow to precipitation under different precipitation scenarios shows that the water level changes in the recharge and drainage areas are similar about (3–5 cm) and slightly larger than that in the runoff area(1.5 cm) when minimum rainfall (287.24 mm) happens. When the precipitation is at its maximum (867.66 mm), the water level change in the runoff area can reach 95 cm which is much larger than those in the recharge and discharge areas. The results indicate that Longzici karst spring has a relatively good regulation water resource capacity and the runoff area is more sensitive which plays an important role in response to climate change. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Water Science / Shuikexue Jinzhan is the property of Editorial Board of Advances in Water Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of the temporal and spatial evolution of precipitation is of great importance for the efficient use of water resources. This paper examines the long series of precipitation in Henan province from 1959-2018. Innovative Trend Analysis (ITA) method and Mann-Kendall (MK) test were used to analyze the characteristics of precipitation trend changes. Mann-Kendall (MK) mutation test and the sliding T method were used to study the jump features of precipitation. Wavelet analysis of the cyclical characteristics of precipitation. The results show that the spatial distribution of precipitation in Henan Province is uneven, with a gradual increase from north to south. The precipitation of northern, central and southern regions showed a downward trend, while that of western regions showed an upward trend. Both the northern and southern regions experienced jump features in precipitation around 1975 and 2008, while the western region experienced jump features around 1962 and 1980, and the central region experienced jump features around 1980; There are 3.5 different scales of “abundance and depletion” in the northern, western and southern regions, with a first principal cycle of 28a, and 5.5 different scales of “abundance and depletion” in the central region, with a first principal cycle of 17a. [ABSTRACT FROM AUTHOR]

Irrigation management consists of many components. In this work we review and recommend rainfall forecast performance metrics and adjoint methodologies for the use of predictive weather data within the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE estimates crop water uses to optimize irrigation scheduling. WISE and its components, input requirements, and related software design issues are discussed. The use of predictive weather allows WISE to consider economic opportunity‐costs of decisions to defer water application if rainfall is forecast. These capabilities require an assessment of the system uncertainties and use of weather prediction performance probabilities. Rainfall forecasts and verification performance metrics are reviewed. In addition, model data assimilation methods and adjoint sensitivity concepts are introduced. These assimilation methods make use of observational uncertainties and can link performance metrics to space and time considerations. We conclude with implementation guidance, summaries of available data sources, and recommend a novel adjoint method to address the complex physical linkages and model sensitivities between space and time within the irrigation scheduling physics as a function of soil depth. Such tool improvements can then be used to improve water management decision performance to better conserve and utilize limited water resources for productive use. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series. Research Impact Statement: Quantitative precipitation forecast data, verification metrics, and adjoint sensitivities are reviewed to advance the quality of irrigation scheduling tools. [ABSTRACT FROM AUTHOR]

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as "how long can a crop water application be delayed while maintaining crop yield production?" are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series. Research Impact Statement: Quantitative precipitation forecast data, verification metrics, and adjoint sensitivities are applied to advance the quality of irrigation scheduling tools. [ABSTRACT FROM AUTHOR]

Recent severe drought events have occurred over the Ogallala Aquifer region (OAR) during the period 2011–2015, creating significant impacts on water resources and their use in regional environmental and economic systems. The changes in terrestrial water storage (TWS), as indicated by the Gravity Recovery and Climate Experiment (GRACE), reveals a detailed picture of the temporal and spatial evolution of drought events. The observations by GRACE indicate the worst drought conditions occurred in September 2012, with an average TWS deficit of ~8 cm in the northern OAR and ~11 cm in the southern OAR, consistent with precipitation data from the Global Precipitation Climatology Project. Comparing changes in TWS with precipitation shows the TWS changes can be predominantly attributable to variations in precipitation. Power spectrum and squared wavelet coherence analysis indicate a significant correlation between TWS change and the El Nino‐Southern Oscillation, and the influence of equatorial Pacific sea surface temperatures on TWS change is much stronger in the southern OAR than the northern OAR. The results of this study illustrate the value of GRACE in not just the diagnosis of significant drought events, but also in possibly improving the predictive power of remote signals that are impacted by nonregional climatic events (El Nino), ultimately leading to improved water resource management applications on a regional scale. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series. Research Impact Statement: The value of GRACE is not just in the diagnosis of drought events but also in the improvement of the predictive power of remote signals, then improving water resource management on a regional scale. [ABSTRACT FROM AUTHOR]

The primary climatic parameter frequently scrutinized in water balance assessments for water utilization is precipitation. Given its considerable variability across locations and over time, it is imperative to rely on high- quality statistical information to facilitate accurate analyses. This study aims to refine the estimation of precipitation data by enhancing information obtained from freely accessible satellite sensors with data collected from established observation stations. Monthly precipitation data spanning from 2000 to 2015 were gathered from 24 stations. Three distinct methodologies were employed to adjust individual station data to address missing data. Consistency analysis and data refinement were conducted for stations requiring adjustments, utilizing graphical analysis and non-parametric statistical techniques. The satellite products under evaluation correspond to the IMERG v6 algorithm. Subsequently, statistical metrics were used to compare observed and estimated data. A correction coefficient was computed by aligning monthly means between observed and calculated data to mitigate random and systemic errors. The IMERG algorithm demonstrates proficiency in accounting for altitude and seasonal variations, with the adjustment significantly enhancing its performance under these conditions. [ABSTRACT FROM AUTHOR]

This study aimed to look for efficient development strategies towards achieving sustainable precipitation management in the Madurai Town Planning Area (MTPA) in India. In the MTPA, precipitation is the predominant source of freshwater for agricultural and domestic uses in addition to water received through conventional systems. The average annual precipitation in the region is ~ 816 mm with standard deviation of 233 mm. The regression analysis showed that annual precipitation is following a decreasing trend and will be about 716 mm by 2030. The Precipitation Concentration Index (PCI) values ranging from 18 to 20 represented strong irregularities and seasonality in annual precipitation over the study area. March, July, September, and November months contributed 2.5, 6.19, 14, and 16% to annual precipitation, respectively, and all showed decreasing trends over time. Only 20% of Northeast monsoon was active over the past 44 years (1976–2019), resulting in a 15% probability of flood and drought occurrences throughout the MTPA. The long-term (1976–2019) average value of annual precipitation days was about 42. The Concentration Index (CI) showed that 60–70% of precipitation was received within 25% of precipitable days. Daily precipitation class of moderate (7.5–34 mm) and rather heavy (34–64 mm) ranges were the dominant types of precipitation, contributing 46% and 26% to total annual precipitation, respectively. Except for October, the monthly precipitation received was deficit to meet the irrigation water demand in the MTPA. However, development of precipitation harvesting systems can annually preserve about 27 Mm3 freshwater in the urban space of the MTPA. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Resources / Ziran Ziyuan Xuebao is the property of Journal of Natural Resources and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Over the past 50 years, there have been significant changes in the runoff process in the Luanhe River basin, exacerbating the scarcity of water resources and their spatiotemporal variability. Therefore, conducting research on the characteristics, trends, and cycles of runoff changes in the Luanhe River basin is of great theoretical and practical significance. This study selected rainfall data from the hydrological stations in Weichang, Chengde, and Qinhuangdao in the Luanhe River basin, covering the period from 1985 to 2008, as well as runoff data from the Hanjiaying, Sandaohezi, and Chengde stations. Based on linear trend regression analysis, the Mann–Kendall rank correlation test, Spearman correlation test, Mann–Kendall method, and Mann–Whitney–Pettitt change point analysis method, this study analyzed the trends in water quantity changes and their change points in the Luanhe River basin. The results of the precipitation at the Weichang and Chengde stations show a non-significant rising trend, remaining relatively stable with slightly increases. Conversely, the precipitation of Qinhuangdao Station shows a decreasing trend over time, albeit non-significant. Considering the detailed diagnostic results from both the Mann–Kendall (M-K) and MWP methods, the change point for Weichang precipitation is identified as 2007, while for Chengde, it spans from 1999 to 2002, and for Qinhuangdao, it is around 1997. The trend of the runoff series of three stations shows a significant decreasing trend and strong significance, and the change point for the annual runoff at the Hanjiaying station and the Sandaohezi station is identified as 2006, and for the Chengde station, the primary change point is 2006, with a secondary change point around 2002. The findings of this research can provide scientific references for the rational development and utilization of regional water resources. [ABSTRACT FROM AUTHOR]

This paper deals with hydrological analyses of Lakes Ohrid and Prespa. The watersheds and the lakes themselves tire shared by three countries: Albania, Greece and Macedonia. As a result of insufficient interstate scientific cooperation and inexistence of data exchange, the lakes and their watersheds are not fully investigated regarding hydrology and hydrogeology. This paper represents a first attempt at a complete hydrological analysis based on data from the Macedonian side. This is not considered to be a particular deficiency, because over 60% of the lakes' watersheds and the lakes themselves belong to Macedonia, where a great number of reliable and long-term data series of hydrometeorological observations exist. The Prespa lakes do not have surface outflow and are connected with Lake Ohrid by underground karst conduits. Because of this, from the hydrological point of view, the lakes and their watersheds cannot be analysed separately. The changes of the regime of the air temperature and the rainfall distribution have been investigated in this report. An increase of the maximum and decrease of the minimum annual air temperatures, as well as a decrease of annual precipitation sums has been determined. Also. a statistically significant descending trend of water level in both lakes has been confirmed, with a statement that the water level decrease in Lake Prespa is extremely alarming. From 1985 to 1995 the water level in Lake Prespa has dropped by more than 5 m, The main reasons for this cannot be identified easily because there are no data on water use quantities from all three countries. As the lakes represent unique natural, ecological and economical water resources in a region suffering water shortage, we plead for a strengthening of international support in activities on salvation of both lakes. A prerequisite for this is the water balance calculation and common cooperation in sustainable water resources management of the lakes. [ABSTRACT FROM AUTHOR]

The variation of lake water storage is an important indicator for studying both climate change and ecological environment changes. Previous studies have mainly focused on the lake storage changes in recent decades, and predicting future lake storage changes on the Tibetan Plateau under climate change scenarios remains a crucial gap. We addressed this gap by establishing prediction models for water storage changes in nine lakes using historical water storage and climate data from the past 29 years and predicting the water storage changes for the next 80 years under three scenarios based on Phase 6 of the Coupled Model Intercomparison Project (CMIP6) data. The Quantile-mapping (QM) method was applied to correct the precipitation data of CMIP6 with assimilated data. The results indicated that the prediction model performed well, with high correlation (R2 > 0.7 for the training set) and low mean absolute error (MSE < 0.1 km3). The results suggest that most lakes will experience a slight increase in water storage until 2050, followed by a rapid rise until 2100 under all three SSP (Shared Socioeconomic Pathways) scenarios, including SSP126, SSP245, and SSP585. By the end of the century, the total projected increase in lake water storage is estimated to be 189.676 ± 16.266 km3, 191.762 ± 10.683 km3, and 186.212 ± 6.441 km3 until 2100, respectively. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are often accompanied by heavy precipitation, which may lead to natural disasters and a serious threat to life and property. However, they also provide indispensable water resources. Studying the temporal and spatial characteristics of TC precipitation is of great importance for TC precipitation forecasting, TC disaster mitigation, and water resource utilization. Guangdong is one of the most frequently and severely TC-affected provinces in China. Due to the different methods used to identify TC precipitation, the conclusions offered by the existing studies are often inconsistent. Moreover, their analyses of the spatiotemporal characteristics of TC precipitation in Guangdong are not sufficiently thorough. In this study, we first selected the historical TCs that affected Guangdong from 1961 to 2020, using an objective separation method for TC wind and rain, based on the observation data from 86 national meteorological stations in Guangdong Province. From these observations covering the past 60 years, the temporal and spatial variations in TC precipitation in Guangdong for four different periods, namely the first rainy season (FRS), the second rainy season (SRS), the non-rainy season (NRS), and over the whole year (WY), were then explored using statistical analysis and multiple cluster methods. The results show that TC frequencies in the four periods all showed a decreasing trend. TC precipitation also showed a decreasing trend in the SRS and NRS, as well as for the WY, but showed a slightly increasing trend in the FRS. Both TC frequency and TC precipitation showed an apparent inter-annual fluctuation and a quasi-periodic pattern. The spatial distribution of TC precipitation in the four periods all showed a decreasing trend from the coastal to the inland stations, but the western coastal areas had higher TC precipitation values than the eastern coastal areas for the SRS, NRS, and WY periods. The spatial variations of TC precipitation in Guangdong in the four periods of the last six decades were quite similar, exhibiting three primary spatial modes and six patterns. Among them, the spatial distribution of TC precipitation being less than normal across the whole province is the most common pattern. The 86 stations can be classified into six groups when using the spatial clustering method and into four groups when using the time-series clustering method. Stations with higher TC precipitation and large inter-annual fluctuations are often distributed in the coastal areas, while stations with less precipitation and small inter-annual fluctuations are distributed in inland areas. However, the primary areas that are affected by TCs may vary in the different periods. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the trends of the annual streamflow and precipitation and cross correlations between them were analyzed in nine large river basins of China during 1956–2005. The results indicate that: (1) the annual mean streamflow decreases in arid and semi-arid regions of north China; however, increasing trends occur in south and Southwest China; (2) the annual streamflow and precipitation exhibit reasonable correlation in nine large river basins except those located in inland areas. The annual streamflow over most areas of China is fed by precipitation; however, the decline in streamflow is faster than the decreases of precipitation since 1970s in the arid and semi-arid regions of north China. The relationship between the annual precipitation and streamflow presents a non-stationary state in north China. This non-stationary relationship is strongly influenced by both human activities and precipitation changes; (3) a significant increase of water use might be the major factor responsible for the steeper decline in streamflow than in precipitation in Haihe River, Yellow River and Songliao River basins in north China. In inland river areas, increase of water use and actual evapotranspiration might result in decline in streamflow although precipitation has an increase tendency. This paper sheds light on the non-stationary relationship between annual precipitation and streamflow and possible underlying causes, which will be helpful for a better understanding of the changes of precipitation and streamflow in China at large scale and in other regions of the world. [Copyright &y& Elsevier]

In the case of changing climate and water crises, the design of every hydraulic structure requires hydrological modeling to investigate the effects of climate change in the region. For this purpose, climate data are the key factor in making a model. However, data scarcity is an issue in developing countries and remote areas. Satellite-based and remote sensing data are an alternative option to be used instead of ground-based meteorological data. Various satellite-based data sets are available to be employed in modeling; nevertheless, the researchers face the challenge of choosing the most precise and reliable data set that should be well suited to the targeted area. In this study, three satellite-based precipitation datasets were investigated using Soil & Water Assessment Tool (SWAT) to analyze their accuracy in the hydrological modeling of the Shakardara watershed, located in the Northwest of Kabul city in Afghanistan. In this research, hydrological modeling was performed using precipitation data from Tropical Rainfall Measurement Mission (TRMM_3B42), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS_v2), and NASA Prediction of Worldwide Energy Resource (NASA POWER) datasets separately. The models were calibrated and validated based on observed river discharge. The acquired result shows the TRMM_3B42 as the most precise and compatible with the region than CHIRPS_v2 and NASA POWER data sets. This research can be used as a reference for hydrologists and water infrastructure designers in the area and other data-scarce regions. [ABSTRACT FROM AUTHOR]

Estimating the groundwater recharge rate is essential in all groundwater-related fields, including groundwater development, use, management, modeling, and contamination analysis. In this study, we proposed a combined method of water budget and climate change scenario for estimating the net groundwater recharge rate in the Nakdong River watershed (NRW), South Korea. For the climate change scenario method, the representative concentration pathway (RCP) 4.5 and 8.5 climate scenarios were adopted. First, using the water budget method from 2009 to 2018, the net groundwater recharge rate (NGRR) of 12.15–18.10% relative to annual precipitation (AP) was obtained, subtracting direct runoff (DR) of 21.18–25.32% relative to AP, evapotranspiration (EP) of 40.53–52.29% relative to AP, and baseflow of 12.42–17.84% relative to AP, from the AP (865–1494 mm). The average annual NGRR of the NRW was 200 mm (15.59%). Second, the mean NGRRs from 2009 to 2100 under the RCP 4.5 and RCP 8.5 scenarios were anticipated as 8.73% and 7.63%, respectively. The similarity between the water budget and climate change scenarios was confirmed using data from 2009 and 2018. According to the simple climate change scenario, it is predicted that annual precipitation will increase over the years while the groundwater level and net groundwater recharge rate will decrease. Nonetheless, the estimated NGRR by the water budget method in this study possesses uncertainty due to using potential ET instead of actual ET which should be estimated by considering soil water content. [ABSTRACT FROM AUTHOR]

The analysis of actual evapotranspiration (ETa) changes is of great significance for the utilization and allocation of water resources. In this study, ETa variability in northern China (aridity index < 0.65) is investigated based on the average of seven datasets (GLEAM, GLASS, a complementary relationship-based dataset, CRA-40, MERRA2, JRA-55, and ERA5-Land). The results show that ETa increases significantly from 1982 to 2017. Limited by water supply, ETa is significantly correlated with precipitation (R = 0.682), whereas the increase in precipitation is insignificant (p = 0.151). Spatially, the long-term trend of ETa is also not completely consistent with that of precipitation. According to a singular value decomposition (SVD) analysis, the trend of ETa is mainly related to the first four leading SVD modes. Homogeneous correlation patterns indicate that more precipitation generally leads to high ETa; however, this relationship is modulated by other factors. Overall, positive potential evapotranspiration anomalies convert more surface water into ETa, resulting in a higher increase in ETa than in precipitation. Specifically, ETa in the northern Tibetan Plateau is associated with meltwater generated by rising temperatures, and ETa in the Badain Jaran Desert is highly dependent on the wet-day frequency. Under global warming, the inconsistency between ETa and precipitation changes has a great impact on water resources in northern China. [ABSTRACT FROM AUTHOR]

Climate change, variability and anthropogenic forcings such as land use change are the main forcings of river discharge variability. However, an understanding of their simultaneous impacts on river discharge remains limited in some parts of the world. To shed light on this issue, the objective of this article is to investigate the effects of rainfall variability and land use change on river discharge in the Nyong basin (at Olama and Mbalmayo gauging stations) and some of its sub-basins (So'o and Mefou) over the long period 1950–2018. To achieve this goal, hydro-meteorological data of the Nyong basin and sub-basins were analyzed using the Pettitt test. Likewise, land use changes in the basin and sub-basins were also analyzed using supervised classifications of Landsat satellite images of the basins at different periods (1973, 2000 and 2018). On the annual scale, rainfall has decreased statistically over the studied basins. In the large basins (Olama and Mbalmayo), this decrease in rainfall is synchronous with that of discharges, while it is concomitant with an increase in the Mefou (small basin). After the ruptures within time series identified in the annual modules, the extreme discharges (maximum and minimum) decreased in Olama; in Mbalmayo, the maximum discharges remained stable while the minimum discharges decreased. On the other hand, the maximum and minimum discharges have significantly increased in the Mefou. The stability of maximum discharges at Mbalmayo and the increase in extremes on the Mefou in a context where the precipitation that generates the discharge has decreased can be attributed to land use change. These changes are essentially marked by an increase in impervious areas and a reduction in forest cover. On the seasonal scale, the impact of precipitation in the dry season is visible on the flows of the rainy seasons that follow them on the large basins (Olama and Mbalmayo). Between the decades 1970–1990 and 2000–2010, there was respectively a significant increase, then a decrease in summer precipitation, which impacted the autumn discharges in the same direction. Conversely, between the same intervals, there was a significant decrease, then a slight increase in winter precipitation. The impact of winter precipitation on the spring discharge is more visible during the first period only (1970–1990). During the second period, winter precipitation seems to have more of an impact on the runoff for the same season. In the Mefou sub-basin, the precipitation plays an essentially amplifying role in the increase in discharge in the seasons during which they occur. Those having experienced an increase, or a maintenance of precipitation (summer and spring) recorded the most significant increases in discharges. These results could be useful for long-term planning on the demand and use of water, as well as flood management in the basins [ABSTRACT FROM AUTHOR]

Recent patterns of water use and supply in California are presented based on a new data set compiled from the California Department of Water Resources water balance data for 2002 through 2016. The water use and supply include surface water and groundwater, although groundwater reporting has been incomplete. These data are used to support the Water Plan released every 3 to 5 years and are the most comprehensive and finest spatial- and temporalscale data set for California water resources. First, using the Bay-Delta watershed as a case example, we show that recent fluctuations in water use are highly correlated with variations in precipitation. Developed water supplies and use show these fluctuations, but they are modified by reservoir inflows and releases, groundwater supplies, and Delta outflows. Second, although the annually precipitated water supply in the Bay-Delta varies by about 30%, the developed water supply damps this considerably. The water management system maintained nearly constant agricultural water use even in periods of intense drought, with year-to-year variation of about 7%. Variability in urban water use is higher (~20%), largely from conservation during periods of drought. Finally, this information can help improve water resource management because it connects regional-scale data to meaningful policy decision-making at county and sub-county levels. At a time when water policy and management are being re-evaluated across the American West in the light of changing climate, decision-making informed by science and data is urgently needed. The statewide water balance data provide the means to establish a consistent, quantitative framework for water resource analysis throughout the state. [ABSTRACT FROM AUTHOR]

The dynamic variations of groundwater have been extensively studied, but there are few studies on the long-term time–frequency features of groundwater dynamic variations. Here we report the dynamic characteristics of the groundwater level and dissolved radon concentration based on the long-term (January 1988–March 2018) daily observation records and regional precipitation data in the Tengchong area, China. The results show that the precipitation (2–3 years and 13 years), groundwater level (13 years), and dissolved radon (9 years) all have multi-year periodic variations, which might be controlled by climate and solar radiation. The groundwater levels were highly correlated with rainfall amount, while the radon concentration variations were not only affected by rainfall but also by other complex factors. Furthermore, the changes of groundwater level and radon concentration lagged behind that of precipitation by about 3 months, and as the cycle range increased, the lag time tended to stabilize. During the observation period, the dissolved radon concentrations increased and decreased sharply. Radon concentration remained correlated with precipitation during the anomalous period. After the anomaly disappeared in 2002, however, its annual periodic characteristics weakened. The increase of radon concentrations may cause a potential risk for water utilization that requires more attention. [ABSTRACT FROM AUTHOR]

This study investigated the attribution of terrestrial water storage (TWS) variations across China to changes in groundwater and human water use. As one vital storage component, the groundwater storage (GWS) derived from the Jet Propulsion Laboratory's GRACE (Gravity Recovery and Climate Experiment) mass concentration solution compared reasonably well with the in situ groundwater table depth, with the correlation coefficients ranging from −0.83 to −0.18, all of which were statistically significant at the 95% confidence level. About 71% of the trends in derived GWS had the same sign as those of observations, without systematic deviation, across China. The GWS variation contributed a large portion of the TWS trend in most regions of China, and the majority of contribution values reached 50%–150% in the Hai River basin, the Loess Plateau, and the middle portion of the Yangtze River basin. The dominant role of GWS is closely related to the detected long-term "memories" in both TWS and GWS. The increase of irrigation consumption accelerated the TWS depletion trend by 13.4% in the Huai River basin, while the decrease of consumptive agricultural water use alleviated the TWS decline rate by 4.1% in the Hai River basin. Importantly, the correlation coefficients reached 0.74–0.95 between the TWS change and the residual of precipitation, evapotranspiration, flow into the sea, and irrigation consumption in the four river basins of particular interest. The findings of this study are helpful for understanding regional water cycles in China. [ABSTRACT FROM AUTHOR]

Watersheds aggregate precipitation signals of many intensities and from many locations into a single observable streamflow at an outlet point. This dependency between precipitation and streamflow varies seasonally and can shift over time due to changes in land cover, climate, human water uses, or changes in properties of precipitation events themselves. We apply information theory‐based measures to capture temporal linkages, or information transfers, from daily precipitation occurrence at different locations in a basin to streamflow at an outlet. We detect critical magnitudes of precipitation and lag times associated with the strongest precipitation‐streamflow relationships, and further partition information transfers to determine relative contributions from the knowledge of wet versus dry past states. Based on an analysis of daily U.S. Geological Survey (USGS) streamflow and Climate Prediction Center (CPC) gridded gauge‐based precipitation data sets in the Colorado Headwaters Basin, this dependency is strongest in fall, the longest dominant lag times occur in spring, and the strengths of dependencies have increased in spring and summer over the past 65 years. These features relate to both seasonal and spatial characteristics of precipitation and the landscape. A partitioning of information components shows that in this basin, the particular knowledge of a lagged, or past, wet state tends to be more informative to flow than a lagged dry state, even though dry days are more frequent. This study introduces several signatures of precipitation‐streamflow relationships that can also more broadly characterize strengths, thresholds, and timescales associated with various interconnected processes. Key Points: Information theory‐based measures detect thresholds, timescales, and strengths of daily precipitation influences on downstream flowsIn the Colorado Headwaters, lagged dependencies are strongest in fall and delays are longest in springA ratio of divergences shows that the knowledge of lagged wet states are on average more informative to streamflow than lagged dry states [ABSTRACT FROM AUTHOR]

Ahn, Jae Hyun and Hyun Il Choi, 2013. A New Flood Index for Use in Evaluation of Local Flood Severity: A Case Study of Small Ungauged Catchments in Korea. Journal of the American Water Resources Association (JAWRA) 49(1): 1-14. DOI: 10.1111/jawr.12025 Abstract: The aim of this article is to develop a new index measuring the severity of floods in small ungauged catchments for initial local flood information by the regression analysis between the new flooding index and rainfall patterns. Although a rapid local flood caused by heavy storm in a short period of time is now one of common natural disasters worldwide, such a sudden and violent hydrologic event is difficult to forecast. As local flooding rises rapidly with little or no advance warning, the key to local flood forecasting is to quickly identify when and where local flooding above a threshold is likely to occur. The new flooding index to characterize local floods is measured by the three normalized relative severity factors for the flood magnitude ratio, the rising curve gradient, and the flooding duration time, quantifying characteristics of flood runoff hydrographs. The new flooding index implemented for the two selected small ungauged catchments in the Korean Peninsula shows a very high correlation with logarithm of the 2-h maximum rainfall depth. This study proposes 30 mm of rainfall in a 2-h period as a basin-specific guidance of precaution for the incipient local flooding in the two study catchments. It is expected that the best-fit regression equation between the new flooding index and a certain rainfall rate can provide preliminary observations, the flood threshold, and severity information, for use in a local flood alert system in small ungauged catchments. Editor's note: This paper is part of a featured series on Korean Hydrology. The series addresses the need for a new paradigm of river and watershed management for Korea due to climate and land use changes. [ABSTRACT FROM AUTHOR]

Precipitation falling in the Snowy Mountains region of south‐east Australia is a critical resource—providing water for hydroelectricity, as well as irrigated agriculture and environmental flows throughout the economically important Murray River system. Improved understanding of the drivers of precipitation variability is therefore a key research aim. Focussing on synoptic types responsible for delivering precipitation ≥10 mm per day, an analysis is presented of the large‐scale atmospheric circulation drivers (“teleconnections”) of seasonal synoptic type frequency using cross‐wavelet and boosted regression tree methods. Results demonstrate that relationships are not stationary over the period 1900–2012, and complex interactions between teleconnections and synoptic atmospheric circulation drive precipitation variability. Importantly, we demonstrate that teleconnections do not act in isolation. Relationships with the tropical Pacific Ocean are shown to be key drivers of synoptic types associated not only with the dominant tropical moisture pathways to the Snowy Mountains, but also with extra‐tropical sources. Tropical sea surface temperatures are therefore shown to drive synoptic type frequency and facilitate the dominance of synoptic types with tropical moisture sources, most notability since the 1950s. [ABSTRACT FROM AUTHOR]

Climate extremes such as droughts and intense rainfall events are expected to strongly influence global/regional water resources in addition to the growing demands for freshwater. This study examines the impacts of precipitation extremes and human water usage on total water storage (TWS) over the Ganges-Brahmaputra-Meghna (GBM) River Basin in South Asia. Monthly TWS changes derived from the Gravity Recovery And Climate Experiment (GRACE) (2002-2014) and soil moisture from three reanalyses (1979-2014) are used to estimate new extreme indices. These indices are applied in conjunction with standardized precipitation indices (SPI) to explore the impacts of precipitation extremes on TWS in the region. The results indicate that although long-term precipitation do not indicate any significant trends over the two subbasins (Ganges and Brahmaputra-Meghna), there is significant decline in rainfall (9.0 ± 4.0 mm/decade) over the Brahmaputra-Meghna River Basin from 1998 to 2014. Both river basins exhibit a rapid decline of TWS from 2002 to 2014 (Ganges: 12.2 ± 3.4 km3/yr and Brahmaputra-Meghna: 9.1 ± 2.7 km3/yr). While the Ganges River Basin has been regaining TWS (5.4 ± 2.2 km3/yr) from 2010 onward, the Brahmaputra-Meghna River Basin exhibits a further decline (13.0 ± 3.2 km3/yr) in TWS from 2011 onward. The impact of human water consumption on TWS appears to be considerably higher in Ganges compared to Brahmaputra-Meghna, where it is mainly concentrated over Bangladesh. The interannual water storage dynamics are found to be strongly associated with meteorological forcing data such as precipitation. In particular, extreme drought conditions, such as those of 2006 and 2009, had profound negative impacts on the TWS, where groundwater resources are already being unsustainably exploited. [ABSTRACT FROM AUTHOR]

Different populations of widely distributed species can experience dramatically different climatic conditions that may influence physiological activity, specifically carbon assimilation and water use. Populus fremontii Wats. (Fremont cottonwood) populations are found near rivers of varying size along a precipitation gradient from New Mexico to northern California. Climatic differences among populations may lead to physiological differences because P. fremontii is sensitive to water availability. To assess physiological variation among populations, we collected foliage and wood samples from 13 populations that experience different precipitation and stream flow regimes and analyzed the samples for carbon isotope composition (δ13C). Wood δ13C served as a lifetime-averaged indicator of water-use efficiency (WUE), whereas foliage δ13C provided as an estimate of WUE during the growing season of collection. We found ∼3.4‰ variation in δ13C among populations for both foliage (–31.1 to –27.9‰) and wood (–28.3 to –24.7‰). Wood δ13C was, on average, 2.8‰ more enriched than foliage. Some of the variation in wood δ13C can be explained by variation in elevation of the study sites. We constructed total precipitation and mean stream flow variables based on the length of the growing season at each study site and analyzed for a relationship between δ13C, precipitation and stream flow. A significant relationship between foliage δ13C and precipitation was found, but water availability did not explain a significant fraction of the variation in wood δ13C. The data suggest that water availability can account for some of the δ13C variation among populations but, given the large residual variances, other factors are important. [ABSTRACT FROM PUBLISHER]

Gediz Basin, located in the western part of Turkey constituting 2% land of the country, has an important groundwater potential in the area. Alasehir sub-basin, located in the southeast of the Gediz Basin and subject to the extensive withdrawal for the irrigation, constitutes the study area. Natural recharge to the sub-basin due to precipitation is numerically investigated in this study. For this purpose, 25 research wells, whose depths range from 20 to 50 m, were drilled to observe the recharge and collect the necessary field data for the numerical model. Meteorological data were collected from 3 weather stations installed in the study area. The numerical model HYDRUS was calibrated using the field water content data. Soil characterization was done on the core samples; the aquifer characterization was performed, and the alluvial aquifer recharge due to precipitation was calculated. As a result, the computed recharge value ranges from 21.78 to 68.52 mm, with an average value of 43.09 mm. According to the numerical model, this amount of recharge corresponds to 10% of the amount of annual rainfall. [ABSTRACT FROM AUTHOR]