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Accounting for Climate Change in Water and Agriculture Management

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A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrology–Climate Interactions".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 15434

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Special Issue Editors

Dr. Md Shahriar Pervez

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Guest Editor

AFDS Contractor to U.S. Geological Survey, Earth Resources Observation and Science Center, Reston, VA 20192, USA
Interests: remote sensing hydrology; land surface models; drought; floods; food security; early warning systems
Special Issues, Collections and Topics in MDPI journals

Dr. Naga Manohar Velpuri

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Guest Editor

ASRC Federal Data Solutions, Contractor to U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57198, USA
Interests: multi-scale watershed hydrologic processes; variability in surface water storage using multi-source satellite data; climate and human impacts on water resources availability, and water availability and use analysis across scales
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The relationships between water, agriculture, and climate are highly interdependent and complex. Weather and climate-related disasters such as droughts, floods, and wildfires are becoming far too common. Over the last decade, the global economic impact of these disasters has increased threefold with hundreds of millions of people experiencing varying degrees of economic losses and food insecurity. Climate change can affect water resources through spatial and temporal variability in precipitation, snow water storage, surface runoff, streamflow, and extreme events, such as droughts and floods. These changes can disrupt agricultural production and threaten global food security. Therefore, monitoring and understanding of hydrometeorological states for potential impacts on agricultural production are key contributors to an early warning of food insecurity. The use of field-based observational techniques is a challenging task at global to regional scales. However, the advances in remote-sensing-based earth observation data, new satellite sensors, and improved climate and land surface modeling techniques are enabling us to monitor, understand, and predict climate change impacts on water availability, agricultural production, and productivity for food security implications.

For this Special Issue, we invite authors to submit research work that details recent advances in climate change impact assessment techniques, especially those methods that have addressed water availability and potential food security applications. We welcome contributions that cover a range from basic science and theories to application studies around the following topics:

Use of surface hydrology models for water resource assessment;
Use of in situ, satellite, and modeled data in surface hydrology models;
Use of satellite and modeled data for drought and flood vulnerability assessments;
Multi-source data assimilation for improved hydrological accounting and forecasting;
Development, improvement, validation, and comparison of hydrometeorological datasets;
Water availability assessment and forecasting;
Basin water accounting methods, forecasting, and applications;
Shifts in precipitation patterns and extremes;
Melting glaciers and snow drought;
Sustainable use of land and water under changing climate;
Climate forecast applications for food security and agricultural management;
Case studies on climate-smart water and agricultural management.

Dr. Md Shahriar Pervez
Dr. Naga Manohar Velpuri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

climate change
droughts
floods
remote sensing hydrology
satellite
precipitation
evapotranspiration
snow drought
modeling
food security
water stress
water availability
early warning

Published Papers (4 papers)

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Research

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15 pages, 3901 KiB

Open AccessArticle

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

by Ramesh Shrestha, Biplob Rakhal, Tirtha Raj Adhikari, Ganesh Raj Ghimire, Rocky Talchabhadel, Dinee Tamang, Radhika KC and Sanjib Sharma

Hydrology 2022, 9(12), 212; https://0-doi-org.brum.beds.ac.uk/10.3390/hydrology9120212 - 28 Nov 2022

Cited by 5 | Viewed by 6018

Abstract

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies. Full article

(This article belongs to the Special Issue Accounting for Climate Change in Water and Agriculture Management)

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19 pages, 2763 KiB

Open AccessArticle

An Integrated Hydrological Modelling Approach to Evaluate the Capacity of Keenjhar Lake by Using STELLA

by Sadaf Sher, Muhammad Waseem, Muhammad Mohsin Waqas, Khawar Rehman, Muhammad Ilyas, Hafiz Ahmed Waqas and Megersa Kebede Leta

Hydrology 2022, 9(5), 90; https://0-doi-org.brum.beds.ac.uk/10.3390/hydrology9050090 - 17 May 2022

Cited by 2 | Viewed by 3340

Abstract

Due to overexploitation and lower rainfall rates, it is essential to study the detailed water balance of the Keenjhar lake by considering the climate change impacts and higher water demands linked with the population growth. A hydrological model of Keenjhar Lake is developed based on a system dynamic approach using STELLA (Structural Thinking and Experiential Learning Laboratory with Animation). The model (STELLA) developed in the current research study comprises the following three sub-systems: population, water supply, and water demand. The hydrological and climate data for the period of seventeen years (2000–2016) is used in the current study. The monthly water budget of the Keenjhar Lake is determined by inflow components such as rainfall and the Kalri-Baghar Feeder (K.B.F) (upper) and outflow components such as evaporation, the K.B. Feeder (lower), and the Keenjhar-Gujju (K.G) canal from the lake. The water balance results revealed that the contribution of direct rainfall and the annual inflow components to the lake are 22.03% and 77.91%, respectively. Whereas the evaporation, outflow to K.B.F lower and water abstraction to the K.G. Canal constituted about 5.78%, 92.55%, and 1.57% of the total annual outflow from the lake, respectively. Moreover, the annual inflow components of the water budget of the lake showed a declining trend while the outflow components (water abstraction) intimated an increasing trend. The study results also acknowledged that the demand for water can increase from 3 × 10¹⁰ ft³/yr up to 1.2 × 10¹¹ ft³/yr by the year 2050 (influence of overdrawing of water due to population growth), and water supply may decrease to 9.066 × 10¹⁰ ft³ (rainfall depletion due to climate change). A detailed water balance explains the main water loss components and will help in developing better water management practices and well-informed policy decisions. Full article

(This article belongs to the Special Issue Accounting for Climate Change in Water and Agriculture Management)

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19 pages, 3022 KiB

Open AccessEditor’s ChoiceArticle

Modeling Water Quantity and Quality Nonlinearities for Watershed Adaptability to Hydroclimate Extremes in Agricultural Landscapes

by Juan Carlos Jaimes-Correa, Francisco Muñoz-Arriola and Shannon Bartelt-Hunt

Hydrology 2022, 9(5), 80; https://0-doi-org.brum.beds.ac.uk/10.3390/hydrology9050080 - 10 May 2022

Cited by 5 | Viewed by 2575

Abstract

Changing water supplies and demands, inherent to climate fluctuations and human activities, are pushing for a paradigm shift in water management worldwide. The occurrence of extreme hydrometeorological and climate events such as extended wet periods and droughts, compounded with contaminants, impair the access to water resources, demanding novel designs, construction, and management across multiple hydrologic scales and biogeochemical processes. A constraint to studying hydrologic and biogeochemical disturbances and improving best management practices for water quantity and quality at the watershed scale resides in the suitable monitoring, data availability, and the creation of frameworks. We hypothesize that streamflow and contaminants, simulated by the hydrologic model Soil and Water Assessment Tool (SWAT) and evaluated during drought and extended wet periods, capture the nonlinearities of contaminants of multiple biogeochemical complexities, indicating the adaptive abilities of watersheds. Our objectives are to (1) use rain gauge and radar data and linear regression to consolidate long-term precipitation data to simulate streamflow and water quality using the SWAT model in the Shell Creek (SC) watershed, Nebraska, U.S.; (2) use drought and extended wet events analytics on observed and simulated hydroclimate and water quality variables to identify SWAT’s performance; and (3) identify the temporal attributions of streamflow and water quality to complex biogeochemical patterns of variability. We implement a watershed modeling approach using the SWAT model forced with rain gauge and radar to simulate the intraseasonal and interannual variability streamflow, sediments, nutrients, and atrazine loads in the SC watershed. SWAT performance uses a calibration period between 2000 and 2005 and a validation period between 2005 and 2007. We examine the model’s ability to simulate hydrologic and biogeochemical variables in response to dry and extended wet flow regimes. The hydrologic model forced by either radar or rain gages performs similarly in the calibration (NSE = 0.6) and validation (NSE = 0.92) periods. It reproduces medium flows closer to the observations, although it overestimates low–flows up to 0.1 m³/s while underestimates high flows by 1 m³/s. The water quality model shows higher NSE for streamflow and sediments followed by nutrients, whereas it poorly reproduces atrazine. We conclude that seasonal changes and hydroclimate conditions led to the emergence of patterns of variability associated to the nonlinearities and coupling between processes of natural and human-origin sources. As climate change propels the occurrence of hydroclimate extremes, the simulation of water quantity and quality nonlinearities—as properties of complex adaptive hydrologic systems—can contribute to improve the predictability of climate-resilient water resources. Full article

(This article belongs to the Special Issue Accounting for Climate Change in Water and Agriculture Management)

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16 pages, 1735 KiB

Open AccessEditor’s ChoiceSystematic Review

Misconceptions of Reference and Potential Evapotranspiration: A PRISMA-Guided Comprehensive Review

by Ali Raza, Nadhir Al-Ansari, Yongguang Hu, Siham Acharki, Dinesh Kumar Vishwakarma, Pouya Aghelpour, Muhammad Zubair, Christine Ajuang Wandolo and Ahmed Elbeltagi

Hydrology 2022, 9(9), 153; https://0-doi-org.brum.beds.ac.uk/10.3390/hydrology9090153 - 24 Aug 2022

Cited by 8 | Viewed by 2548

Abstract

One of the most important parts of the hydrological cycle is evapotranspiration (ET). Accurate estimates of ET in irrigated regions are critical to the planning, control, and regulation of agricultural natural resources. Accurate ET estimation is necessary for agricultural irrigation scheduling. ET is a nonlinear and complex process that cannot be calculated directly. Reference evapotranspiration (RET) and potential evapotranspiration (PET) are two primary forms of ET. The ideas, equations, and application areas for PET and RET are different. These two terms have been confused and used interchangeably by researchers. Therefore, terminology clarification is necessary to ensure their proper use. The research indicates that PET and RET concepts have a long and distinguished history. Thornthwaite devised the original PET idea, and it has been used ever since, although with several improvements. The development of RET, although initially confused with that of PET, was formally defined as a standard method. In this study, the Preferred Reporting Item for Systematic reviews and Meta-Analysis (PRISMA) was used. Equations for RET estimation were retrieved from 44 research articles, and equations for PET estimation were collected from 26 studies. Both the PET and RET equations were divided into three distinct categories: temperature-based, radiation-based, and combination-based. The results show that, among temperature-based equations for PET, Thornthwaite’s (1948) equation was mentioned in 12,117 publications, whereas among temperature-based equations for RET, Hargreaves and Samani’s (1985) equation was quoted in 3859 studies. Similarly, Priestley (1972) had the most highly cited equation in radiation-based PET equations (about 6379), whereas Ritchie (1972) had the most highly cited RET equations (around 2382) in radiation-based equations. Additionally, among combination-based PET equations, Penman and Monteith’s (1948) equations were cited in 9307 research studies, but the equations of Allen et al. (1998) were the subject of a significant number of citations from 23,000 publications. Based on application, PET is most often applied in the fields of hydrology, meteorology, and climatology, whereas RET is more frequently utilized in the fields of agronomy, agriculture, irrigation, and ecology. PET has been used to derive drought indices, whereas RET has been employed for single crop and dual crop coefficient approaches. This work examines and describes the ideas and methodologies, widely used equations, applications, and advanced approaches associated with PET and RET, and discusses future enhancements to increase the accuracy of ET calculation to attain accurate agricultural irrigation scheduling. The use of advanced tools such as remote sensing and satellite technologies, in addition to machine learning algorithms, will help to improve the accuracy of PET and RET estimates. Researchers will be able to distinguish between PET and RET in the future with the use of the study’s results. Full article

(This article belongs to the Special Issue Accounting for Climate Change in Water and Agriculture Management)

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