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Assessment of Spatial and Temporal Variability of Water Resources
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Assessment of Spatial and Temporal Variability of Water Resources

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 74766

Special Issue Editor

Dr. Ilyas Masih

E-Mail Website
Guest Editor
IHE Delft Institute for Water Education, Delft The Netherlands, P.O. Box 3015, 2601 DA Delft, The Netherlands
Interests: catchment hydrology; water resources assessment in well-gauged, poorly gauged and ungauged catchments; spatial and temporal variability of water resources; impact of global changes (e.g., climate and land use changes) on water resources; drought assessment and management; integrated water resources planning and management; sustainable development
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Special Issue Information

Dear Colleagues,

Sustainable water resources management occupies a prominent position in the global agenda. Improved knowledge on water resources availability, including their spatial and temporal variability, is pivotal to making progress towards sustainable development. Despite scientific progress in hydrology and water resources assessment, the current knowledge on water availability across a range of spatial and temporal scales (e.g., global, regional, river basin, inter- and intra-annual variability) is still limited, especially in view of the rapidly changing world. Water availability is changing both spatially and temporally because of the natural hydro-climatic variability and of global changes triggered by anthropogenic factors. This Special Issue aims to contribute to advancing the scientific knowledge related to water resources variability and availability. Original and novel contributions are invited for this Special Issue, with specific focus on the following topics:

  • Global, regional, country- and river basin-level assessments of water resources variability and availably
  • Advances and application of modelling techniques to assess the spatio-temporal variability of water resources
  • Application of statistical techniques (e.g., flow duration and trend detection) to assess variability, assurance, and trends in water resources
  • Assessment of water resources in poorly gauged and ungauged basins
  • An integrated analysis of various data sources, i.e., field monitoring and remote sensing, to assess water resources
  • Spatial and temporal variability of hydrological extremes (flood and droughts)
  • Impact of global changes on water resources, including but not limited to, climate, land use, and socio-economic changes
  • Integrating spatial and temporal variability of water resources into sustainable water resources planning and management

The submissions may cover the above-mentioned or related issues in the form of a review, synthesis, or case study research. The accepted papers will be published in open access, ensuring widespread availability, according to the policy of MDPI, which is a well-recognized open access publisher with growing impact.

Dr. Ilyas Masih
Guest Editor

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Keywords

  • water resources
  • spatial and temporal variability
  • integrated use of ground and remotely sensed data
  • water resources assessment
  • hydrological modelling
  • trend analysis
  • water availability
  • global change impact
  • sustainable water resources development

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Published Papers (17 papers)

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Research

25 pages, 2648 KiB  
Article
The Impacts of Climate Variability on Crop Yields and Irrigation Water Demand in South Asia
by Qurat-ul-Ain Ahmad, Hester Biemans, Eddy Moors, Nuzba Shaheen and Ilyas Masih
Water 2021, 13(1), 50; https://doi.org/10.3390/w13010050 - 29 Dec 2020
Cited by 21 | Viewed by 6507
Abstract
Accurate (spatio-temporal) estimation of the crop yield relation to climate variables is essential in the densely populated Indus, Ganges, and Brahmaputra (IGB) river basins of South Asia for devising appropriate adaptation strategies to ensure regional food and water security. This study examines wheat [...] Read more.
Accurate (spatio-temporal) estimation of the crop yield relation to climate variables is essential in the densely populated Indus, Ganges, and Brahmaputra (IGB) river basins of South Asia for devising appropriate adaptation strategies to ensure regional food and water security. This study examines wheat (Triticum aestivum) and rice (Oryza sativa) crop yields’ sensitivity to primary climate variables (i.e., temperature and precipitation) and related changes in irrigation water demand at different spatial (i.e., province/state, districts and grid cell) and temporal (i.e., seasonal and crop growth phase) scales. To estimate the climate driven variations in crop yields, observed and modelled data applying the Lund-Potsdam-Jena managed Land (LPJmL) model are used for six selected study sites in the IGB river basins over the period 1981–2010. Our statistical analysis underscores the importance of impacts assessments at higher spatio-temporal scales. Our grid cell (aggregated over study sites) scale analysis shows that 27–72% variations in wheat and 17–55% in rice crop yields are linked with temperature variations at a significance level of p < 0.001. In the absence of irrigation application, up to 39% variations in wheat and up to 75% variations in rice crop yields are associated with precipitation changes in all study sites. Whereas, observed crop yields show weak correlations with temperature at a coarser resolution, i.e., up to 4% at province and up to 31% at district scales. Crop yields also showed stronger sensitivity to climate variables at higher temporal scale (i.e., vegetative and reproductive phases) having statistically strong negative relationship with temperature and positive with precipitation during the reproductive phase. Similarly, crop phase-specific variations in climate variables have considerable impacts (i.e., quantity and timing) on irrigation water demand. For improved crop water planning, we suggest integrated climate impact assessments at higher spatio-temporal scales which can help to devise appropriate adaptation strategies for sustaining future food demand. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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16 pages, 5948 KiB  
Article
Spatiotemporal Distribution Characteristics of Reference Evapotranspiration in Shandong Province from 1980 to 2019
by Fujie Zhang, Zihan Liu, Lili Zhangzhong, Jingxin Yu, Kaili Shi and Li Yao
Water 2020, 12(12), 3495; https://doi.org/10.3390/w12123495 - 12 Dec 2020
Cited by 11 | Viewed by 2549
Abstract
Reference evapotranspiration (ET0) is an important part of the water cycle and energy cycle during crop growth. Understanding the influencing factors and spatiotemporal variations of ET0 can guide regional water-saving irrigation and regulate agricultural production. Data for daily meteorological observations [...] Read more.
Reference evapotranspiration (ET0) is an important part of the water cycle and energy cycle during crop growth. Understanding the influencing factors and spatiotemporal variations of ET0 can guide regional water-saving irrigation and regulate agricultural production. Data for daily meteorological observations of temperature, relative humidity, wind speed, and sunshine hours from 38 surface meteorological stations were used to analyze the spatiotemporal variations and trends in Shandong Province from 1980 to 2019. (1) The ET0 from 1980 to 2019 was 1070.5 mm, and there was a significant downward trend in the climate tendency rate of −7.92/10 a. The climate of Shandong Province became warmer and drier. The average annual temperature showed a significant upward trend, while the average annual relative humidity and average annual sunshine hours showed significant downward trends. (2) The annual ET0 ratio in spring, summer, autumn, and winter was 29%, 40%, 21%, and 10%, respectively. (3) A change in Shandong Province’s interannual ET0 occurred in 2002, with a decrease of 130.74 mm since then. (4) The ET0 was positively correlated with temperature, wind speed, and sunshine hours and negatively correlated with relative humidity. This study provides a scientific basis for the regulation and control of agricultural production in Shandong Province. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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18 pages, 11596 KiB  
Article
Automated Mapping of Water Table for Cranberry Subirrigation Management: Comparison of Three Spatial Interpolation Methods
by Paul Celicourt, Silvio Jose Gumiere, Jonathan A. Lafond, Thiago Gumiere, Jacques Gallichand and Alain N. Rousseau
Water 2020, 12(12), 3322; https://doi.org/10.3390/w12123322 - 26 Nov 2020
Cited by 13 | Viewed by 4571
Abstract
In this paper we first compare three different methods of spatial interpolation, i.e., inverse distance weighting (IDW), thin plate splines (TPS), and kriging on weekly water table depth (WTD) measurements from 80 observation wells in two cranberry farms (Farm A and Farm B) [...] Read more.
In this paper we first compare three different methods of spatial interpolation, i.e., inverse distance weighting (IDW), thin plate splines (TPS), and kriging on weekly water table depth (WTD) measurements from 80 observation wells in two cranberry farms (Farm A and Farm B) located in Québec, Canada. We use the leave-one-out cross-validation approach to assess the performance of the methods. Second, we evaluate the influence of the density of measurement points over the interpolation error for the cited methods. Third, we assess the performance of drainage systems and their impacts on crop productivity as a result of cumulative rainfall. Results along with practical considerations show that TPS is the best interpolator for WTD and this superiority is maintained and further demonstrated through a sensitivity analysis of the methods to spatial sampling density, i.e., partitioning the data into subsets of 25, 50, and 75% of the dataset. However, the random approach for selecting these subsets shows an unexpected result; that is, the interpolation methods exhibit a higher performance in terms of the Pearson correlation (r) for the 25% data subset at Farm B. Meanwhile, the cumulative precipitation over a three-day period, the maximum time required to return the soil matric potential to the optimal value after a major rainfall event, had a steady influence on WTD and thus crop productivity in the studied farms. This influence is more apparent for Farm A, but a rather random effect is noted for Farm B. This study presents a water-management-based strategy that mitigates the supplementary cost and effort for sensor deployment in water table monitoring for cranberry production. It is therefore of practical interest to cranberry growers and decision-makers who aim to maximize yields through water-management-oriented strategies. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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20 pages, 4491 KiB  
Article
Quantitative Detection and Attribution of Groundwater Level Variations in the Amu Darya Delta
by Xiaohui Pan, Weishi Wang, Tie Liu, Yue Huang, Philippe De Maeyer, Chenyu Guo, Yunan Ling and Shamshodbek Akmalov
Water 2020, 12(10), 2869; https://doi.org/10.3390/w12102869 - 15 Oct 2020
Cited by 13 | Viewed by 4398
Abstract
In the past few decades, the shrinkage of the Aral Sea is one of the biggest ecological catastrophes caused by human activity. To quantify the joint impact of both human activities and climate change on groundwater, the spatiotemporal groundwater dynamic characteristics in the [...] Read more.
In the past few decades, the shrinkage of the Aral Sea is one of the biggest ecological catastrophes caused by human activity. To quantify the joint impact of both human activities and climate change on groundwater, the spatiotemporal groundwater dynamic characteristics in the Amu Darya Delta of the Aral Sea from 1999 to 2017 were analyzed, using the groundwater level, climate conditions, remote sensing data, and irrigation information. Statistics analysis was adopted to analyze the trend of groundwater variation, including intensity, periodicity, spatial structure, while the Pearson correlation analysis and principal component analysis (PCA) were used to quantify the impact of climate change and human activities on the variabilities of the groundwater level. Results reveal that the local groundwater dynamic has varied considerably. From 1999 to 2002, the groundwater level dropped from −189 cm to −350 cm. Until 2017, the groundwater level rose back to −211 cm with fluctuation. Seasonally, the fluctuation period of groundwater level and irrigation water was similar, both were about 18 months. Spatially, the groundwater level kept stable within the irrigation area and bare land but fluctuated drastically around the irrigation area. The Pearson correlation analysis reveals that the dynamic of the groundwater level is closely related to irrigation activity within the irrigation area (Nukus: −0.583), while for the place adjacent to the Aral Sea, the groundwater level is closely related to the Large Aral Sea water level (Muynak: 0.355). The results of PCA showed that the cumulative contribution rate of the first three components exceeds 85%. The study reveals that human activities have a great impact on groundwater, effective management, and the development of water resources in arid areas is an essential prerequisite for ecological protection. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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19 pages, 11125 KiB  
Article
Divergent Trends of Water Storage Observed via Gravity Satellite across Distinct Areas in China
by Panxing He, Zongjiu Sun, Zhiming Han, Xiaoliang Ma, Pei Zhao, Yifei Liu and Jun Ma
Water 2020, 12(10), 2862; https://doi.org/10.3390/w12102862 - 14 Oct 2020
Cited by 12 | Viewed by 3256
Abstract
Knowledge of the spatiotemporal variations of terrestrial water storage (TWS) is critical for the sustainable management of water resources in China. However, this knowledge has not been quantified and compared for the different climate types and underlying surface characteristics. Here, we present observational [...] Read more.
Knowledge of the spatiotemporal variations of terrestrial water storage (TWS) is critical for the sustainable management of water resources in China. However, this knowledge has not been quantified and compared for the different climate types and underlying surface characteristics. Here, we present observational evidence for the spatiotemporal dynamics of water storage based on the products from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS) in China over 2003–2016. Our results were the following: (1) gravity satellite dataset showed divergent trends of TWS across distinct areas due to human factors and climate factors. The overall changing trend of water storage is that the north experiences a loss of water and the south gains in water, which aggravates the uneven spatial distribution of water resources in China. (2) In the eastern monsoon area, the depletion of water storage in North China (NC) was found to be mostly due to anthropogenic disturbance through groundwater pumping in plain areas. However, precipitation was shown to be a key driver for the increase of water storage in South China (SC). Increasing precipitation in SC was linked to atmospheric circulation enhancement and Pacific Ocean warming, meaning an unrecognized teleconnection between circulation anomalies and water storage. (3) At high altitudes in the west, the change of water storage was affected by the melting of ice and snow due to the rising temperatures, yet the topography determines the trend of water storage. We found that the mountainous terrain led to the loss of water storage in Tianshan Mountain (TSM), while the closed basin topography gathered the melted water in the interior of the Tibetan Plateau (ITP). This study highlights the impacts of the local climate and topography on terrestrial water storage, and has reference value for the government and the public to address the crisis of water resources in China. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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15 pages, 9219 KiB  
Article
Assessing the Climate Tendency over the Yangtze River Delta, China: Properties, Dry/Wet Event Frequencies, and Causes
by Yanfei Wu and Yu Xu
Water 2020, 12(10), 2734; https://doi.org/10.3390/w12102734 - 30 Sep 2020
Cited by 3 | Viewed by 2253
Abstract
In view of the important role to in revealing climate wet/dry tendency, Standardized Precipitation Index (SPI) was applied to identify wetness/dryness trends and their relationship with large-scale climate oscillations in the Yangtze River Delta (YRD) from 1957 to 2016. The daily precipitation in [...] Read more.
In view of the important role to in revealing climate wet/dry tendency, Standardized Precipitation Index (SPI) was applied to identify wetness/dryness trends and their relationship with large-scale climate oscillations in the Yangtze River Delta (YRD) from 1957 to 2016. The daily precipitation in 43 meteorological stations was used to calculate SPI time series for a time scale of 12 months. The results indicate that there are three dominant geographic sub-regions of SPI-12 modes. Increasing trends dominate, except for some of the northern regions. High frequencies of wet and dry events are mainly located in the southern regions and part of the northwestern and southeastern regions, respectively. Temporally, large-scale dry events mainly happened in the 1960s–1970s, and wet events in the 1990s and the 2010s. They show a tendency towards more wet conditions of the regional climate in the YRD. The climate variations are primarily controlled by large-scale atmospheric oscillations. The North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI) have much higher influence on the variation of SPI in the mid and east; whereas the Pacific Decadal Oscillation (PDO) and North Pacific Index (NP) show higher correlations with SPI in the northern regions of the YRD. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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15 pages, 3250 KiB  
Article
A Simple Time-Varying Sensitivity Analysis (TVSA) for Assessment of Temporal Variability of Hydrological Processes
by Yelena Medina and Enrique Muñoz
Water 2020, 12(9), 2463; https://doi.org/10.3390/w12092463 - 2 Sep 2020
Cited by 4 | Viewed by 3581
Abstract
Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational [...] Read more.
Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational cost, as it estimates sensitivity in a moving window within an analyzed series, performing a series of repetitive calculations. In this article a function to implement a simple TVSA with a low computational cost using regional sensitivity analysis is presented. As an example of its application, an analysis of hydrological model results in daily, monthly, and annual time windows is carried out. The results show that the model allows the time sensitivity of a model with respect to its parameters to be detected, making it a suitable tool for the assessment of temporal variability of processes in models that include time series analysis. In addition, it is observed that the size of the moving window can influence the estimated sensitivity; therefore, analysis of different time windows is recommended. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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21 pages, 7119 KiB  
Article
Global BROOK90 R Package: An Automatic Framework to Simulate the Water Balance at Any Location
by Ivan Vorobevskii, Rico Kronenberg and Christian Bernhofer
Water 2020, 12(7), 2037; https://doi.org/10.3390/w12072037 - 17 Jul 2020
Cited by 13 | Viewed by 5624
Abstract
The number of global open-source hydrometeorological datasets and models is large and growing. However, with a constantly growing demand for services and tools from stakeholders, not only in the water sector, we still lack simple solutions, which are easy to use for nonexperts. [...] Read more.
The number of global open-source hydrometeorological datasets and models is large and growing. However, with a constantly growing demand for services and tools from stakeholders, not only in the water sector, we still lack simple solutions, which are easy to use for nonexperts. The new R package incorporates the BROOK90 hydrologic model and global open-source datasets used for parameterization and forcing. The aim is to estimate the vertical water fluxes within the soil–water–plant system of a single site or of a small catchment (<100 km2). This includes data scarce regions where no hydrometeorological measurements or reliable site characteristics can be obtained. The end-user only needs to provide a location and the desired period. The package automatically downloads the necessary datasets for elevation (Amazon Web Service Terrain Tiles), land cover (Copernicus: Land Cover 100 m), soil characteristics (ISRIC: SoilGrids250), and meteorological forcing (Copernicus: ERA5 reanalysis). Subsequently these datasets are processed, specific hydrotopes are created, and BROOK90 is applied. In a last step, the output data of all desired variables on a daily scale as well as time-series plots are stored. A first daily and monthly validation based on five catchments within various climate zones shows a decent representation of soil moisture, evapotranspiration, and runoff components. A considerably better performance is achieved for a monthly scale. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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20 pages, 6176 KiB  
Article
Teleconnections between Monthly Rainfall Variability and Large-Scale Climate Indices in Southwestern Colombia
by Teresita Canchala, Wilfredo Alfonso-Morales, Wilmar Loaiza Cerón, Yesid Carvajal-Escobar and Eduardo Caicedo-Bravo
Water 2020, 12(7), 1863; https://doi.org/10.3390/w12071863 - 29 Jun 2020
Cited by 21 | Viewed by 3936
Abstract
Given that the analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research [...] Read more.
Given that the analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research topic. It should also be noted that little-to-no research has been carried out on this topic before. For the purpose of conducting this research, we identified homogeneous rainfall regions while using Non-Linear Principal Component Analysis (NLPCA) and Self-Organizing Maps (SOM). The rainfall variability modes were obtained from the NLPCA, while their teleconnection in relation to the climate indices was obtained from Pearson’s Correlations and Wavelet Transform. The regionalization process clarified that Nariño has two regions: the Andean Region (AR) and the Pacific Region (PR). The NLPCA showed two modes for the AR, and one for the PR, with an explained variance of 75% and 48%, respectively. The correlation analyses between the first nonlinear components of AR and PR regarding climate indices showed AR high significant positive correlations with Southern Oscillation Index (SOI) index and negative correlations with El Niño/Southern Oscillation (ENSO) indices. PR showed positive ones with Niño1 + 2, and Niño3, and negative correlations with Niño3.4 and Niño4, although their synchronous relationships were not statistically significant. The Wavelet Coherence analysis showed that the variability of the AR rainfall was influenced principally by the Niño3.4 index on the 3–7-year inter-annual scale, while PR rainfall were influenced by the Niño3 index on the 1.5–3-year inter-annual scale. The El Niño (EN) events lead to a decrease and increase in the monthly rainfall on AR and PR, respectively, while, in the La Niña (LN) events, the opposite occurred. These results that are not documented in previous studies are useful for the forecasting of monthly rainfall and the planning of water resources in the area of study. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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23 pages, 2861 KiB  
Article
Analyses of Precipitation and Evapotranspiration Changes across the Lake Kyoga Basin in East Africa
by Charles Onyutha, Grace Acayo and Jacob Nyende
Water 2020, 12(4), 1134; https://doi.org/10.3390/w12041134 - 16 Apr 2020
Cited by 20 | Viewed by 4383
Abstract
This study analyzed changes in CenTrends gridded precipitation (1961–2015) and Potential Evapotranspiration (PET; 1961–2008) across the Lake Kyoga Basin (LKB). PET was computed from gridded temperature of the Princeton Global Forcings. Correlation between precipitation or PET and climate indices was analyzed. PET in [...] Read more.
This study analyzed changes in CenTrends gridded precipitation (1961–2015) and Potential Evapotranspiration (PET; 1961–2008) across the Lake Kyoga Basin (LKB). PET was computed from gridded temperature of the Princeton Global Forcings. Correlation between precipitation or PET and climate indices was analyzed. PET in the Eastern LKB exhibited an increase (p > 0.05). March–April–May precipitation decreased (p > 0.05) in most parts of the LKB. However, September–October–November (SON) precipitation generally exhibited a positive trend. Rates of increase in the SON precipitation were higher in the Eastern part where Mt. Elgon is located than at other locations. Record shows that Bududa district at the foot of Mt. Elgon experienced a total of 8, 5, and 6 landslides over the periods 1818–1959, 1960–2009, and 2010–2019, respectively. It is highly probable that these landslides have recently become more frequent than in the past due to the increasing precipitation. The largest amounts of variance in annual precipitation (38.9%) and PET (41.2%) were found to be explained by the Indian Ocean Dipole. These were followed by precipitation (17.9%) and PET (21.9%) variance explained by the Atlantic multidecadal oscillation, and North Atlantic oscillation, respectively. These findings are vital for predictive adaptation to the impacts of climate variability on water resources. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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19 pages, 2994 KiB  
Article
Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey
by Taner Mustafa Cengiz, Hossein Tabari, Charles Onyutha and Ozgur Kisi
Water 2020, 12(3), 705; https://doi.org/10.3390/w12030705 - 5 Mar 2020
Cited by 25 | Viewed by 3897
Abstract
Many statistical methods have been developed and used over time to analyze historical changes in hydrological time series, given the socioeconomic consequences of the changes in the water cycle components. The classical statistical methods, however, rely on many assumptions on the time series [...] Read more.
Many statistical methods have been developed and used over time to analyze historical changes in hydrological time series, given the socioeconomic consequences of the changes in the water cycle components. The classical statistical methods, however, rely on many assumptions on the time series to be examined such as the normality, temporal and spatial independency and the constancy of the data distribution over time. When the assumptions are not fulfilled by the data, test results are not reliable. One way to relax these cumbersome assumptions and credibilize the results of statistical approaches is to make a combined use of graphical and statistical methods. To this end, two graphical methods of the refined cumulative sum of the difference between exceedance and non-exceedance counts of data points (CSD) and innovative trend analyses (ITA)-change boxes alongside the classical statistical Mann–Kendall (MK) method are used to analyze historical precipitation changes at 16 stations during 1960–2015 in the Black Sea region of Turkey. The results show a good match between the results of the graphical and statistical methods. The graphical CSD and ITA methods, however, are able to identify the hidden trends in the precipitation time series that cannot be detected using the statistical MK method. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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23 pages, 8851 KiB  
Article
Streamflow Variability in Colombian Pacific Basins and Their Teleconnections with Climate Indices
by Teresita Canchala, Wilmar Loaiza Cerón, Félix Francés, Yesid Carvajal-Escobar, Rita Valéria Andreoli, Mary Toshie Kayano, Wilfredo Alfonso-Morales, Eduardo Caicedo-Bravo and Rodrigo Augusto Ferreira de Souza
Water 2020, 12(2), 526; https://doi.org/10.3390/w12020526 - 13 Feb 2020
Cited by 26 | Viewed by 5228
Abstract
Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows [...] Read more.
Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows in the ARB and PRB and the oceanic-atmospheric factors have not been examined considering different temporal scales. Hence, this article studies the relations of the climate indices and the variability of the streamflows in the ARB and PRB at interannual and decadal timescales. To this, the streamflow variability modes were obtained from the principal component analysis (PCA); furthermore, their linear dependence with indices of the El Niño/Southern Oscillation (ENSO), precipitation (PRP), the Choco low-level jet (CJ), and other indices were quantified through (a) Pearson and Kendall’s tau correlations, and (b) wavelet transform. The PCA presented a single significant mode for each basin, with an explained variance of around 80%. The correlation analyses between the PC1s of the ARB and PRB, and the climate indices showed significant positive (negative) high correlations with PRP, CJ, and Southern Oscillation Index (SOI) (ENSO indices). The wavelet coherence analysis showed significant coherencies between ENSO and ARB: at interannual (2–7 years) and decadal scale (8–14), preferably with the sea surface temperature (SST) in the east and west Tropical Pacific Ocean (TPO). For PRB with the SST in the central and western regions of the TPO in the interannual (4–8 years) and decadal (8–14 years) scales, the decreases (increases) in streamflow precede the El Niño (La Niña) events. These results indicate multiscale relations between the basins’ streamflow and climate phenomena not documented in previous works, relevant to forecast the extreme flow events in the Colombian Pacific rivers and for planning and implementing strategies for the sustainable use of water resources in the basins studied. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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12 pages, 2409 KiB  
Article
Spatial and Temporal Investigation of Dew Potential based on Long-Term Model Simulations in Iran
by Nahid Atashi, Dariush Rahimi, Behnam M. Goortani, Jonathan Duplissy, Henri Vuollekoski, Markku Kulmala, Timo Vesala and Tareq Hussein
Water 2019, 11(12), 2463; https://doi.org/10.3390/w11122463 - 23 Nov 2019
Cited by 8 | Viewed by 4620
Abstract
Since water shortage has been a serious challenge in Iran, long-term investigations of alternative water resources are vital. In this study, we performed long-term (1979–2018) model simulation at seven locations (costal, desert, mountain, and urban conditions) in Iran to investigate temporal and spatial [...] Read more.
Since water shortage has been a serious challenge in Iran, long-term investigations of alternative water resources are vital. In this study, we performed long-term (1979–2018) model simulation at seven locations (costal, desert, mountain, and urban conditions) in Iran to investigate temporal and spatial variation of dew formation. The model was developed to simulate the dew formation (water and ice) based on the heat and mass balance equation with ECMWF-ERA-Interim (European Centre for Medium-Range Weather Forecasts–Re-Analysis) meteorological data as input. According to the model simulation, the maximum mean yearly cumulative dew yield (~65 L/m2) was observed in the mountain region in the north part of Iran with a yearly mean cumulative dew yield was ~36 L/m2. The dew yield showed a clear seasonal variation at all selected locations with maximum yields in winter (mean monthly cumulative 3–8 L/m2 depending on the location). Here we showed that dew formation is frequent in northern Iran. In other areas, where there was suffering from water-stress (southern and central parts of Iran), dew can be a utilized as an alternative source of water. The dew yield during 2001–2014 was lower than the overall mean during the past 40 years a result of climate change in Iran. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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16 pages, 4036 KiB  
Article
Space–Time Kriging of Precipitation: Modeling the Large-Scale Variation with Model GAMLSS
by Elias Silva de Medeiros, Renato Ribeiro de Lima, Ricardo Alves de Olinda, Leydson G. Dantas and Carlos Antonio Costa dos Santos
Water 2019, 11(11), 2368; https://doi.org/10.3390/w11112368 - 12 Nov 2019
Cited by 18 | Viewed by 4076
Abstract
Knowing the dynamics of spatial–temporal precipitation distribution is of vital significance for the management of water resources, in highlight, in the northeast region of Brazil (NEB). Several models of large-scale precipitation variability are based on the normal distribution, not taking into consideration the [...] Read more.
Knowing the dynamics of spatial–temporal precipitation distribution is of vital significance for the management of water resources, in highlight, in the northeast region of Brazil (NEB). Several models of large-scale precipitation variability are based on the normal distribution, not taking into consideration the excess of null observations that are prevalent in the daily or even monthly precipitation information of the region under study. This research proposes a novel way of modeling the trend component by using an inflated gamma distribution of zeros. The residuals of this regression are generally space–time dependent and have been modeled by a space–time covariance function. The findings show that the new techniques have provided reliable and precise precipitation estimates, exceeding the techniques used previously. The modeling provided estimates of precipitation in nonsampled locations and unobserved periods, thus serving as a tool to assist the government in improving water management, anticipating society’s needs and preventing water crises. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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21 pages, 7508 KiB  
Article
Characteristics and Drivers of Reference Evapotranspiration in Hilly Regions in Southern China
by Youcun Liu, Yan Liu, Ming Chen, David Labat, Yongtao Li, Xiaohui Bian and Qianqian Ding
Water 2019, 11(9), 1914; https://doi.org/10.3390/w11091914 - 14 Sep 2019
Cited by 9 | Viewed by 2980
Abstract
This paper has adopted related meteorological data collected by 69 meteorological stations between 1951 and 2013 to analyze changes and drivers of reference evapotranspiration (ET0) in the hilly regions located in southern China. Results show that: (1) ET0 in southern [...] Read more.
This paper has adopted related meteorological data collected by 69 meteorological stations between 1951 and 2013 to analyze changes and drivers of reference evapotranspiration (ET0) in the hilly regions located in southern China. Results show that: (1) ET0 in southern China’s hilly regions reaches its maximum in summer and its minimum in winter, and that the annual ET0 shows an increasing trend. ET0 happened abrupt change due to the impact of abrupt meteorological variables changes, and the significant year of mutation were 1953, 1964 and 2008. Most abrupt changes of ET0 in meteorological stations occurred in the 1950s and 1960s. (2) The low value of ET0 was mainly captured in high-altitude areas. Spatially, the ET0 in the east was higher than that in the west. With the exception of a handful of stations, the trend coefficients of ET0 were all positive, exhibiting a gradual rise. Changes in ET0 in the east were much more sensitive than that in the west. Since ET0 was affected by the cyclical changes in relative humidity, short-period oscillations were observed in all these changes. (3) In general, the ET0 was negatively correlated with relative humidity, and positively correlated with temperature and sunshine percentage. ET0 is most sensitive to changes in average temperature, with a sensitivity coefficient of 1.136. ET0 showed positive sensitivity to average temperature and sunshine hours, which were notable in the northeastern, and uniform in the spatial. ET0 showed negatively sensitivity to relative humidity, and the absolute value of sensitivity coefficient in the northwestern is smaller. The highest contribution to ET0 is the average temperature (6.873%), and the total contribution of the four meteorological variables to the change of ET0 is 7.842%. The contribution of average temperature, relative humidity, and sunshine hours to ET0 is higher in the northern and eastern, northern, northern and eastern areas, respectively. Climate indexes (Western Pacific Index (WP), Southern Oscillation Index (SOI), Tropical Northern Atlantic Index (TNA), and El Niño-Southern Oscillation (ENSO)) were correlated with the ET0. In addition, the ET0 and altitude, as well as the latitude and longitude were also correlated with each other. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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25 pages, 5857 KiB  
Article
Estimation of Base Flow by Optimal Hydrograph Separation for the Conterminous United States and Implications for National-Extent Hydrologic Models
by Sydney S. Foks, Jeff P. Raffensperger, Colin A. Penn and Jessica M. Driscoll
Water 2019, 11(8), 1629; https://doi.org/10.3390/w11081629 - 7 Aug 2019
Cited by 18 | Viewed by 6080
Abstract
Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) [...] Read more.
Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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20 pages, 4674 KiB  
Article
Influencing Factors of the Spatial–Temporal Variation of Layered Soils and Sediments Moistures and Infiltration Characteristics under Irrigation in a Desert Oasis by Deterministic Spatial Interpolation Methods
by Xin Li, Yudong Lu, Xiaozhou Zhang, Rong Zhang, Wen Fan and Wangsheng Pan
Water 2019, 11(7), 1483; https://doi.org/10.3390/w11071483 - 17 Jul 2019
Cited by 6 | Viewed by 3640
Abstract
Soil moisture is the main limiting factor for crop growth and the sustainable development of oases in arid desert areas. Therefore, the temporal and spatial variation and infiltration laws of oasis soil moisture should be studied. The objective of this study is to [...] Read more.
Soil moisture is the main limiting factor for crop growth and the sustainable development of oases in arid desert areas. Therefore, the temporal and spatial variation and infiltration laws of oasis soil moisture should be studied. The objective of this study is to reveal the influencing factors of the spatial–temporal variation of layered soil and sediment moisture and infiltration characteristics under irrigation in desert oases. Hydraulic conductivities were measured using the double-ring infiltrometer, while the regional and site soil moistures were measured and calibrated using weighted method and neutron moisture meter. Deterministic spatial interpolation methods, including multiquadric radial basis function, inverse distance weighted, and local polynomial regression isogram, were adopted to map the regional distribution of hydraulic conductivities, spatial soil moistures, and spatial–temporal isogram of the point site soil moistures in Yaoba Oasis, respectively. Results showed that the leading influencing factors of the (1) regional spatial soil moisture were soil and sediment permeability, stream link direction, microclimate, and dewfalls; (2) spatial layered soil and sediment moistures were microclimate and dew condensation; and (3) spatial–temporal variation at the point site profiles were soil texture, water requirement, and preferential flow. Under irrigation, soil moisture increased significantly, in which the maximum increase was 10.8 times the original state, while the recharging depth substantially increased up to 580 cm with the preferential flow. The spatial–temporal variation of the soil moisture under irrigation indicated that the best irrigation frequency should be 15 days per time. Moreover, the infiltration process can be divided into the preferential flow, piston flow, and balanced infiltration stages. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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