Management Of Water Resources In Areas Research Articles

Does the performance enhancement through multi-model averaging at the catchment outlet gets translated to the interior ungauged points?

Accurate prediction of streamflow is essential at both the outlet and interior points for effective water resource management. This study aimed to investigate whether improved simulation results at the catchment outlet through Multi-Model Averaging (MMA) can be translated to interior ungauged points in a catchment. To achieve this, the study considered ensemble combinations of 81 conceptual hydrologic models and calibrated each model using four objective functions for two study areas (Jagdalpur and Wardha subbasins of Godavari basin). Six MMA methods were applied to evaluate their performance at interior points in the catchment. The findings revealed that, when compared to the best performing hydrologic model, the best MMA method showed an improvement in terms of Nash-Sutcliffe efficiency, ranging from 2.2% to 3.8% at the interior point of Jagdalpur and 2% to 12% at the interior points of Wardha. MMA methods with KGE-calibrated models as input exhibited better performance in terms of NSE, while those using LogarithmicNSE-calibrated and parent models as input ensembles showed better performance in terms of Percentage bias and Skill Score. Bayesian model averaging and Genetic Algorithm based averaging methods were identified as the most appropriate MMA methods, and the study findings suggest that the performance of these techniques varies at different interior points based on their spatial and temporal variation of flow characteristics. Overall, this study would be beneficial for better flow prediction at internal ungauged points, which is crucial for effective water resource management in areas where there is limited data or where new developments have occurred.

Prediction of profile soil moisture for one land use using measurements at a soil depth of other land uses in a karst depression

Information on root-zone soil water content (SWC) is essential for vegetation restoration, irrigation scheduling, and hydrological modeling. However, measurements of SWC within a variety of land uses may be time-consuming and labor-costing. This study tested whether SWC at a depth of a land use can be used to predict profile SWC of other land uses in terms of temporal stability analysis at a karst depression area in southwest China. A total of 30 datasets of root-zone SWC from 0.1- to 0.5-m depths were collected by time domain reflectometry probes for three typical land uses from March 12 to November 8, 2015. Results showed that the profile mean SWC and its associated standard deviation (SDP) and coefficient of variation (CVP) differed significantly (P < 0.05) among the grassland, farmland, and forestland. The profile SWC was more temporally stable according to the apparently lower CVT in comparison with CVP. The similarities of the vertical patterns of SWC were strong for the same land uses, while were relatively weak between the different land uses. The SWC measurements of the most temporally stable depth can be used to accurately predict profile SWC for both the same land use and other land uses. This study further expands the application of the temporal stability analysis and can aid water resource management in areas with diverse land uses.

An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources

Water resources in coastal areas can be profoundly influenced by both climate change and human activities. These climatic and human impacts are usually intertwined and difficult to isolate. This study developed an integrated model-based approach for detection and attribution of climatic and human impacts and applied this approach to the Luanhe Plain, a typical coastal area in northern China. An integrated surface water-groundwater model was developed for the study area using GSFLOW (coupled groundwater and surface-water flow). Model calibration and validation were performed for background years between 1975 and 2000. The variation in water resources between the 1980s and 1990s was then quantitatively attributed to climate variability, groundwater pumping and changes in upstream inflow. Climate scenarios for future years (2075–2100) were also developed by downscaling the projections in CMIP5. Potential water resource responses to climate change, as well as their uncertainty, were then investigated through integrated modeling. The study results demonstrated the feasibility and value of the integrated modeling-based analysis for water resource management in areas with complex surface water-groundwater interaction. Specific findings for the Luanhe Plain included the following: (1) During the historical period, upstream inflow had the most significant impact on river outflow to the sea, followed by climate variability, whereas groundwater pumping was the least influential. (2) The increase in groundwater pumping had a dominant influence on the decline in groundwater change, followed by climate variability. (3) Synergetic and counteractive effects among different impacting factors, while identified, were not significant, which implied that the interaction among different factors was not very strong in this case. (4) It is highly probable that future climate change will accelerate groundwater depletion in the study area, implying that strict regulations for groundwater pumping are imperative for adaptation.

Managing Drought Through Water Markets: Farmer Preferences in the Rio Grande Basin1

Abstract: Managing drought in agriculture has taken on growing importance as population growth and environmental concerns place increasing pressures on agricultural water use. One alternative for agricultural water resource management in areas of recurrent drought is allocation through market mechanisms. While past research has aimed to explain why farmers are reluctant to participate in already established water markets, this research seeks to identify the appropriate market mechanism given farmers’ preexisting attitudes toward water markets. Statistical analysis of survey data from 166 farmer interviews in the Rio Grande Basin indicate that farmers are significantly more likely to participate in short‐term water mechanisms, such as spot water markets and water banks than in permanent transfer mechanisms, particularly those that fully separate water rights from land. In sharp contrast to expectations, the choice of market mechanism did not differ significantly between farmers based on their a priori intention to buy, sell or both buy and sell in these markets. Choice of market mechanism also did not differ among farmer types although small, lifestyle or hobby farmers clearly preferred spot water markets to other types of short‐term mechanisms. Evaluating these attitudes a priori may help to design more suitable water market mechanisms for the basin.