Development of a distributed water circulation model for assessing human interaction in agricultural water use

Iizumi

et al. 2015

Paddy Water Environ

Rice productivity will be affected by climate conditions not only in own region but also in neighboring regions through technological spillover. Measuring such direct and indirect influence of future climate change is important for policy making. This study analyzes socioeconomic and climate factors in rice total factor productivity (TFP) and evaluates technological spillover effects by using the spatial econometric model. To consider geographical situation, we use hydrological model in addition to crop-yield and crop-quality models. Results show that spatial autoregressive tendencies were observed in rice TFP, even though the influences of climate factors were removed. Such spatial dependence brings about synergistic effects among neighboring prefectures in northern Japan and depression effects, like a spatial trap, from neighbors in southern Japan. Substantial impacts of climate change were as high as socio-economic factors but different in degrees by regions. Also, future climate change estimated by the global climate model enlarged fluctuation degree in rice TFP because accumulative or cancel out effects of temperature and precipitation occurred year by year. Therefore, technological development in rice production and provision of precise climate prediction to farmers are important in order to ease and mitigate these influences.Keywords Crop model Á Hydrological model Á Rice total factor productivity (TFP) Á Spatial lag model Á Research and development activities JEL code C21 Á Q54 Á R11 Á R15

Section: Climate Indexesmentioning

confidence: 99%

Technological spillover in Japanese rice productivity under long-term climate change: evidence from the spatial econometric model

Kunimitsu

Iizumi

et al. 2015

Paddy Water Environ

“…The distributed water circulation model incorporating agricultural water use (DWCM-AgWU; Masumoto et al, 2009;Taniguchi et al, 2009) was used to model the Pursat River Basin, taking into account an assessment method of the effects of climate change on agricultural water use.…”

Section: Basin-scale Irrigation Planning For the Pursat River Basinmentioning

confidence: 99%

Basin‐Scale Irrigation Planning in Areas with Scarce Data

Masumoto

Yoshida

Irrigation and Drainage

2016

This paper presents a basin-scale approach to irrigation planning for use in areas with scarce hydrological and meteorological data. We review the past development of cascade irrigation facilities in Cambodia's Kep Province and present the results of applying a distributed water circulation model that incorporates agricultural water use in Cambodia's Pursat River Basin. Basic hydrological and meteorological data are scarce for these areas, partly as a result of the Cambodian civil war. Although 70% of overall water use is for agriculture, irrigation rates in many areas of monsoonal Asia are low and farming depends mainly on rainwater, even in basins where paddy fields are dominant and water resources are abundant. Moreover, basic hydrological and meteorological data are scarce in these areas. Past irrigation planning proposals in these areas have not specified the required volumes of water or the necessary capacities of irrigation facilities. Our consideration of irrigation projects in the Pursat River Basin, based on meteorological data inputs estimated by using a general circulation and/or climate change model, showed that basin-scale irrigation planning can be applied despite the scarcity of data. RÉSUMÉAlors que 70% de l'utilisation de l'eau est. destinée à l'agriculture, le rapport d'irrigation dans beaucoup de régions de l'Asie affectées par la Mousson est. très bas même dans les régions où les rizières dominent et où les ressources en eau sont réputées comme abondantes. En outre, même si lorsque l'on a planifié le programme d'irrigation dans lesdites zones, les observations sur les données fondamentales météorologiques et hydrographiques sont très peu nombreuses. Avec la manière conventionnelle de proposer une irrigation, il n'est. pas possible de décider des volumes requis des ressources en eau pour les installations en question. Par contre, dans cet exposé nous avons eu pour but de proposer de nouvelles propositions et de différentes approches pour irriguer un grand bassin global dans le but de développer « un grand bassin pour une planification généralisée ». Cette étude est. basée sur l'exemple des installations d'irrigation en cascade dans la Province de Kep au Cambodge et du plan d'utilisation des ressources en eau dans le bassin de Pursat situé dans la province éponyme au Cambodge. En raison de la guerre civile entre autres facteurs, il n'existe pas de données concernant ces secteurs et à l'heure présente l'agriculture dépend principalement des précipitations. Nous avons proposé cette nouvelle approche pour proposer une planification de l'irrigation basée sur l'impact sur l'environnement prenant en compte les changements climatiques sur l'utilisation de l'eau à des fins agricoles dans des ré-gions où l'on possède très peu de données.

“…1). The model used is based on Masumoto et al (2009) and Yoshida et al (2012). CFI is measured as the total unit outflow per terrain mesh area during the typhoon season in August and September as follows:…”

Section: Climate Factorsmentioning

confidence: 99%

“…Amid global warming, heavy rain is becoming increasingly frequent and serious in Japan (Nakakita et al 2011). The rainfall pattern is also supposed to change by future climate change, whereupon Japanese rice productivity will be affected by severe floods caused by heavy rain and poorly drained surface water from long rain.…”

Section: Introductionmentioning

confidence: 99%

Fluctuations in Rice Productivity Caused by Long and Heavy Rain Under Climate Change in Japan: Evidence from Panel Data Regression Analysis

Kunimitsu

2015

JARQ

The incidence of extreme rain is expected to increase with climate change and affect rice productivity in Japan. This study aims to evaluate the impacts of long and heavy rain on Japanese rice total-factor productivity (TFP) by estimating causality functions. We measured rice TFP by using the Törnqvist-Theil and Malmquist indexes for dependent variables and predicted, the influences of future temperature and rain on rice TFP by the causality function associated with crop models and a hydrological model based on climate projections from the global-climate model (GCM). The results initially showed no significant differences between Törnqvist-Theil and Malmquist indices in the effects of climate factors, although some differences emerged in the causality of socioeconomic factors. Second, the effects of rain were always negative, and absolute TFP elasticity against rain was lower than temperature via yield and quality, but poorly drained surface water as well as flooding reduced rice TFP by 2.5 to 4.5%. Third, changes in predicted rainfall under future climate change caused annual rice TFP to fluctuate, and an impact of rain on TFP fluctuations exceeded that of temperature via yield and quality. This is due to significant variations in annual rainfall, even though the measured elasticity against rain was low. Based on these findings, the implications for research and policy-making are discussed.