Long-Term Climate Modeling and Hydrological Projection

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 8437

Special Issue Editor


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Guest Editor
Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada
Interests: planning of energy and environmental systems; synchrotron-based environmental chemistry and biochemistry; climate modeling and downscaling; simulation of hydrological and environmental systems
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Special Issue Information

Dear Colleagues,

Climate change has significant impacts on water resource systems. Such impacts may involve the hydrological cycle and the related human interests, such as water supply, drought prevention, and flooding control. With the effects of climate change, planning for various water-related infrastructure will also need to be updated. Therefore, long-term climate modeling and hydrological projection are essential for supporting the improvements of such plans.

This Special Issue encourages contributions of (1) coupled models for long-term hydroclimate simulation; (2) hydrologic impacts based on long-term climate projections, driven by GCMs, RCMs, and statistical downscaling models; (3) adaptation of climate-change impacts on the hydrological cycle, associated with the analyses of their socioeconomic and environmental effects; and (4) reflection of uncertainties in long-term climate modeling and hydrological projection, as well as the relevant efforts for adaptation planning.

Prof. Dr. Gordon Huang
Guest Editor

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Keywords

  • climate change
  • climate dynamics
  • statistical downscaling
  • uncertainties
  • extreme events
  • hydrological cycle
  • water resources management
  • droughts
  • floods

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Published Papers (2 papers)

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Research

17 pages, 2284 KiB  
Article
Influence of Climate Conditions on the Temporal Development of Wheat Yields in a Long-Term Experiment in an Area with Pleistocene Loess
by Kurt Heil, Anna Lehner and Urs Schmidhalter
Climate 2020, 8(9), 100; https://doi.org/10.3390/cli8090100 - 27 Aug 2020
Cited by 14 | Viewed by 3836
Abstract
Field experiments were conducted to test different agronomic practices, such as soil cultivation, fertilization, and pest and weed management, in highly controlled plot cultivation. The inter-annual yields and the interpretation of such experiments is highly affected by the variability of climatic conditions and [...] Read more.
Field experiments were conducted to test different agronomic practices, such as soil cultivation, fertilization, and pest and weed management, in highly controlled plot cultivation. The inter-annual yields and the interpretation of such experiments is highly affected by the variability of climatic conditions and fertilization level. We examined the effect of different climate indices, such as winterkill, late spring frost, early autumn frost, different drought parameters, precipitation-free periods, and heat-related stress, on winter wheat yield. This experiment was conducted in an agricultural area with highly fertile conditions, characterized by a high available water capacity and considerable C and N contents in lower soil depths. Residuals were calculated from long-term yield trends with a validated method (time series autoregressive integrated moving average ARIMA) and these served as base values for the detection of climate-induced, short-term, and inter-annual variations. In a subsequent step, the real yield values were used for their derivations from climate factors. Residuals and real yields were correlated with climate variables in multiple regression of quantitative analyses of the yield sensitivity. The inter-annual variation of yields varied considerably within the observation period. However, the variation was less an effect of the climatic conditions during the main growing time periods, being more of an effect of the prevailing climate conditions in the winter period as well as of the transition periods from winter to the warmer season and vice versa. The high storage capacity of plant available water exerted a remarkable dampening effect on drought-induced effects during the main vegetation periods. Increasing fertilization led to increased susceptibility to drought stress. The results indicate a changed picture of the yield development in these fertile locations. Full article
(This article belongs to the Special Issue Long-Term Climate Modeling and Hydrological Projection)
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19 pages, 2881 KiB  
Article
Monitoring Hydrometeorological Droughts Using a Simplified Precipitation Index
by Abdullah A. Alsumaiei
Climate 2020, 8(2), 19; https://doi.org/10.3390/cli8020019 - 23 Jan 2020
Cited by 11 | Viewed by 3754
Abstract
Efficient water management plans should rely on quantitative metrics for assessing water resource shortage scenarios. This study develops a simplified precipitation index (PI) requiring precipitation data only in order to assess hydrometeorological droughts affecting various hydrological systems. The PI index is [...] Read more.
Efficient water management plans should rely on quantitative metrics for assessing water resource shortage scenarios. This study develops a simplified precipitation index (PI) requiring precipitation data only in order to assess hydrometeorological droughts affecting various hydrological systems. The PI index is inspired by the famous Standardized Precipitation Index (SPI), and it aims to provide the same indication for drought severity and duration while overcoming the disadvantage of needing hydrological data normalization. Avoiding hydrological data normalization overcomes the non-satisfactory results of this procedure that were reported in previous studies. Analysis of groundwater drought drivers in the arid region of Kuwait is presented to test the index applicability at timescales 12 and 24 months using available historical precipitation data from 1958 to 2017. A bivariate joint probability analysis was conducted by Clayton copula to assess the occurrence of certain drought severities and durations. The results showed that PI is comparable to the original SPI and provides drought severity linearly propagating with respect to time. This index constitutes a simple means to help water managers assess and describe the impact of droughts in precipitation-controlled systems and establish appropriate water management plans. Full article
(This article belongs to the Special Issue Long-Term Climate Modeling and Hydrological Projection)
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